ConcurrentWorkflow
Overview
The ConcurrentWorkflow swarm type runs independent tasks in parallel, significantly reducing processing time for complex operations. This architecture is ideal for tasks that can be processed simultaneously without dependencies, allowing multiple agents to work on different aspects of a problem at the same time. Key features:- Parallel Execution: Multiple agents work simultaneously
- Reduced Processing Time: Faster completion through parallelization
- Independent Tasks: Agents work on separate, non-dependent subtasks
- Scalable Performance: Performance scales with the number of agents
Architecture
All agents start at once and work independently. No agent waits on another.Use Cases
- Independent data analysis tasks
- Parallel content generation
- Multi-source research projects
- Distributed problem solving
API Usage
Basic ConcurrentWorkflow Example
- Shell (curl)
- Python (requests)
- JavaScript (fetch)
- Go
- Rust
curl -X POST "https://api.swarms.world/v1/swarm/completions" \
-H "x-api-key: $SWARMS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "Market Research Concurrent",
"description": "Parallel market research across different sectors",
"swarm_type": "ConcurrentWorkflow",
"task": "Research and analyze market opportunities in AI, healthcare, fintech, and e-commerce sectors",
"agents": [
{
"agent_name": "AI Market Analyst",
"description": "Analyzes AI market trends and opportunities",
"system_prompt": "You are an AI market analyst. Focus on artificial intelligence market trends, opportunities, key players, and growth projections.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "Healthcare Market Analyst",
"description": "Analyzes healthcare market trends",
"system_prompt": "You are a healthcare market analyst. Focus on healthcare market trends, digital health opportunities, regulatory landscape, and growth areas.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "Fintech Market Analyst",
"description": "Analyzes fintech market opportunities",
"system_prompt": "You are a fintech market analyst. Focus on financial technology trends, digital payment systems, blockchain opportunities, and regulatory developments.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "E-commerce Market Analyst",
"description": "Analyzes e-commerce market trends",
"system_prompt": "You are an e-commerce market analyst. Focus on online retail trends, marketplace opportunities, consumer behavior, and emerging platforms.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
}
],
"max_loops": 1
}'
import os
import requests
import json
from dotenv import load_dotenv
load_dotenv()
API_BASE_URL = "https://api.swarms.world"
API_KEY = os.getenv("SWARMS_API_KEY")
headers = {
"x-api-key": API_KEY,
"Content-Type": "application/json"
}
swarm_config = {
"name": "Market Research Concurrent",
"description": "Parallel market research across different sectors",
"swarm_type": "ConcurrentWorkflow",
"task": "Research and analyze market opportunities in AI, healthcare, fintech, and e-commerce sectors",
"agents": [
{
"agent_name": "AI Market Analyst",
"description": "Analyzes AI market trends and opportunities",
"system_prompt": "You are an AI market analyst. Focus on artificial intelligence market trends, opportunities, key players, and growth projections.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "Healthcare Market Analyst",
"description": "Analyzes healthcare market trends",
"system_prompt": "You are a healthcare market analyst. Focus on healthcare market trends, digital health opportunities, regulatory landscape, and growth areas.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "Fintech Market Analyst",
"description": "Analyzes fintech market opportunities",
"system_prompt": "You are a fintech market analyst. Focus on financial technology trends, digital payment systems, blockchain opportunities, and regulatory developments.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "E-commerce Market Analyst",
"description": "Analyzes e-commerce market trends",
"system_prompt": "You are an e-commerce market analyst. Focus on online retail trends, marketplace opportunities, consumer behavior, and emerging platforms.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
}
],
"max_loops": 1
}
response = requests.post(
f"{API_BASE_URL}/v1/swarm/completions",
headers=headers,
json=swarm_config
)
if response.status_code == 200:
result = response.json()
print("ConcurrentWorkflow swarm completed successfully!")
print(f"Cost: ${result['usage']['billing_info']['total_cost']}")
print(f"Execution time: {result['execution_time']} seconds")
print(f"Parallel results: {result['output']}")
else:
print(f"Error: {response.status_code} - {response.text}")
const API_BASE_URL = "https://api.swarms.world";
const API_KEY = "your_api_key_here";
const headers = {
"x-api-key": API_KEY,
"Content-Type": "application/json"
};
const swarmConfig = {
name: "Market Research Concurrent",
description: "Parallel market research across different sectors",
swarm_type: "ConcurrentWorkflow",
task: "Research and analyze market opportunities in AI, healthcare, fintech, and e-commerce sectors",
agents: [
{
agent_name: "AI Market Analyst",
description: "Analyzes AI market trends and opportunities",
system_prompt: "You are an AI market analyst. Focus on artificial intelligence market trends, opportunities, key players, and growth projections.",
model_name: "gpt-4.1",
max_loops: 1,
temperature: 0.3
},
{
agent_name: "Healthcare Market Analyst",
description: "Analyzes healthcare market trends",
system_prompt: "You are a healthcare market analyst. Focus on healthcare market trends, digital health opportunities, regulatory landscape, and growth areas.",
model_name: "gpt-4.1",
max_loops: 1,
temperature: 0.3
},
{
agent_name: "Fintech Market Analyst",
description: "Analyzes fintech market opportunities",
system_prompt: "You are a fintech market analyst. Focus on financial technology trends, digital payment systems, blockchain opportunities, and regulatory developments.",
model_name: "gpt-4.1",
max_loops: 1,
temperature: 0.3
},
{
agent_name: "E-commerce Market Analyst",
description: "Analyzes e-commerce market trends",
system_prompt: "You are an e-commerce market analyst. Focus on online retail trends, marketplace opportunities, consumer behavior, and emerging platforms.",
model_name: "gpt-4.1",
max_loops: 1,
temperature: 0.3
}
],
max_loops: 1
};
fetch(`${API_BASE_URL}/v1/swarm/completions`, {
method: "POST",
headers: headers,
body: JSON.stringify(swarmConfig)
})
.then(response => response.json())
.then(result => {
if (result.status === "success") {
console.log("ConcurrentWorkflow swarm completed successfully!");
console.log(`Cost: $${result.usage.billing_info.total_cost}`);
console.log(`Execution time: ${result.execution_time} seconds`);
console.log("Parallel results:", result.output);
}
})
.catch(error => console.error("Error:", error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
type Agent struct {
AgentName string `json:"agent_name"`
Description string `json:"description"`
SystemPrompt string `json:"system_prompt"`
ModelName string `json:"model_name"`
MaxLoops int `json:"max_loops"`
Temperature float64 `json:"temperature"`
}
type SwarmConfig struct {
Name string `json:"name"`
Description string `json:"description"`
SwarmType string `json:"swarm_type"`
Task string `json:"task"`
Agents []Agent `json:"agents"`
MaxLoops int `json:"max_loops"`
}
func main() {
API_BASE_URL := "https://api.swarms.world"
API_KEY := "your_api_key_here"
swarmConfig := SwarmConfig{
Name: "Market Research Concurrent",
Description: "Parallel market research across different sectors",
SwarmType: "ConcurrentWorkflow",
Task: "Research and analyze market opportunities in AI, healthcare, fintech, and e-commerce sectors",
Agents: []Agent{
{
AgentName: "AI Market Analyst",
Description: "Analyzes AI market trends and opportunities",
SystemPrompt: "You are an AI market analyst. Focus on artificial intelligence market trends, opportunities, key players, and growth projections.",
ModelName: "gpt-4.1",
MaxLoops: 1,
Temperature: 0.3,
},
{
AgentName: "Healthcare Market Analyst",
Description: "Analyzes healthcare market trends",
SystemPrompt: "You are a healthcare market analyst. Focus on healthcare market trends, digital health opportunities, regulatory landscape, and growth areas.",
ModelName: "gpt-4.1",
MaxLoops: 1,
Temperature: 0.3,
},
{
AgentName: "Fintech Market Analyst",
Description: "Analyzes fintech market opportunities",
SystemPrompt: "You are a fintech market analyst. Focus on financial technology trends, digital payment systems, blockchain opportunities, and regulatory developments.",
ModelName: "gpt-4.1",
MaxLoops: 1,
Temperature: 0.3,
},
{
AgentName: "E-commerce Market Analyst",
Description: "Analyzes e-commerce market trends",
SystemPrompt: "You are an e-commerce market analyst. Focus on online retail trends, marketplace opportunities, consumer behavior, and emerging platforms.",
ModelName: "gpt-4.1",
MaxLoops: 1,
Temperature: 0.3,
},
},
MaxLoops: 1,
}
jsonData, _ := json.Marshal(swarmConfig)
req, _ := http.NewRequest("POST", API_BASE_URL+"/v1/swarm/completions", bytes.NewBuffer(jsonData))
req.Header.Set("x-api-key", API_KEY)
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
fmt.Printf("Error: %v\n", err)
return
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Printf("Response: %s\n", string(body))
}
use reqwest::Client;
use serde_json::{json, Value};
use std::error::Error;
#[tokio::main]
async fn main() -> Result<(), Box<dyn Error>> {
let api_base_url = "https://api.swarms.world";
let api_key = "your_api_key_here";
let swarm_config = json!({
"name": "Market Research Concurrent",
"description": "Parallel market research across different sectors",
"swarm_type": "ConcurrentWorkflow",
"task": "Research and analyze market opportunities in AI, healthcare, fintech, and e-commerce sectors",
"agents": [
{
"agent_name": "AI Market Analyst",
"description": "Analyzes AI market trends and opportunities",
"system_prompt": "You are an AI market analyst. Focus on artificial intelligence market trends, opportunities, key players, and growth projections.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "Healthcare Market Analyst",
"description": "Analyzes healthcare market trends",
"system_prompt": "You are a healthcare market analyst. Focus on healthcare market trends, digital health opportunities, regulatory landscape, and growth areas.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "Fintech Market Analyst",
"description": "Analyzes fintech market opportunities",
"system_prompt": "You are a fintech market analyst. Focus on financial technology trends, digital payment systems, blockchain opportunities, and regulatory developments.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
},
{
"agent_name": "E-commerce Market Analyst",
"description": "Analyzes e-commerce market trends",
"system_prompt": "You are an e-commerce market analyst. Focus on online retail trends, marketplace opportunities, consumer behavior, and emerging platforms.",
"model_name": "gpt-4.1",
"max_loops": 1,
"temperature": 0.3
}
],
"max_loops": 1
});
let client = Client::new();
let response = client
.post(&format!("{}/v1/swarm/completions", api_base_url))
.header("x-api-key", api_key)
.header("Content-Type", "application/json")
.json(&swarm_config)
.send()
.await?;
if response.status().is_success() {
let result: Value = response.json().await?;
println!("ConcurrentWorkflow swarm completed successfully!");
println!("Response: {:?}", result);
} else {
println!("Error: {}", response.status());
}
Ok(())
}
{
"job_id": "swarms-S17nZFDesmLHxCRoeyF3NVYvPaXk",
"status": "success",
"swarm_name": "Market Research Concurrent",
"description": "Parallel market research across different sectors",
"swarm_type": "ConcurrentWorkflow",
"output": [
{
"role": "E-commerce Market Analyst",
"content": "To analyze market opportunities in the AI, healthcare, fintech, and e-commerce sectors, we can break down each sector's current trends, consumer behavior, and emerging platforms. Here's an overview of each sector with a focus on e-commerce....."
},
{
"role": "AI Market Analyst",
"content": "The artificial intelligence (AI) landscape presents numerous opportunities across various sectors, particularly in healthcare, fintech, and e-commerce. Here's a detailed analysis of each sector:\n\n### Healthcare....."
},
{
"role": "Healthcare Market Analyst",
"content": "As a Healthcare Market Analyst, I will focus on analyzing market opportunities within the healthcare sector, particularly in the realm of AI and digital health. The intersection of healthcare with fintech and e-commerce also presents unique opportunities. Here's an overview of key trends and growth areas:...."
},
{
"role": "Fintech Market Analyst",
"content": "Certainly! Let's break down the market opportunities in the fintech sector, focusing on financial technology trends, digital payment systems, blockchain opportunities, and regulatory developments:\n\n### 1. Financial Technology Trends....."
}
],
"number_of_agents": 4,
"execution_time": 23.360230922698975,
"usage": {
"input_tokens": 35,
"output_tokens": 2787,
"total_tokens": 2822,
"billing_info": {
"cost_breakdown": {
"agent_cost": 0.04,
"input_token_cost": 0.000114,
"output_token_cost": 0.02578,
"token_counts": {
"total_input_tokens": 35,
"total_output_tokens": 2787,
"total_tokens": 2822
},
"num_agents": 4,
"night_time_discount_applied": true
},
"total_cost": 0.065894,
"discount_active": true,
"discount_type": "night_time",
"discount_percentage": 50
}
}
}
Output Shape
Every swarm run is executed through aSwarmRouter with output_type forced to "dict" server-side (see api/swarm_completions.py), so output is a list of {"role": ..., "content": ...} conversation turns rather than a single string. For ConcurrentWorkflow specifically, each requested agent receives the same original task independently and runs on a thread pool — there is one turn per agent, but because the agents run in parallel rather than a fixed sequence, the order turns land in output reflects when each agent finished, not the order the agents appear in the request.
Best Practices
- Design independent tasks that don’t require sequential dependencies
- Use for tasks that can be parallelized effectively
- Ensure agents have distinct, non-overlapping responsibilities
- Ideal for time-sensitive analysis requiring multiple perspectives