curl -X POST "https://api.swarms.world/v1/swarm/completions" \
-H "x-api-key: $SWARMS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "Product Strategy Discussion",
"description": "Collaborative chat to develop product strategy",
"swarm_type": "GroupChat",
"task": "Discuss and develop a go-to-market strategy for a new AI-powered productivity tool targeting small businesses",
"agents": [
{
"agent_name": "Product Manager",
"description": "Leads product strategy and development",
"system_prompt": "You are a senior product manager. Focus on product positioning, features, user needs, and market fit. Ask probing questions and build on others ideas.",
"model_name": "gpt-4o",
"max_loops": 3,
},
{
"agent_name": "Marketing Strategist",
"description": "Develops marketing and positioning strategy",
"system_prompt": "You are a marketing strategist. Focus on target audience, messaging, channels, and competitive positioning. Contribute marketing insights to the discussion.",
"model_name": "gpt-4o",
"max_loops": 3,
},
{
"agent_name": "Sales Director",
"description": "Provides sales and customer perspective",
"system_prompt": "You are a sales director with small business experience. Focus on pricing, sales process, customer objections, and market adoption. Share practical sales insights.",
"model_name": "gpt-4o",
"max_loops": 3,
},
{
"agent_name": "UX Researcher",
"description": "Represents user experience and research insights",
"system_prompt": "You are a UX researcher specializing in small business tools. Focus on user behavior, usability, adoption barriers, and design considerations.",
"model_name": "gpt-4o",
"max_loops": 3,
}
],
"max_loops": 3
}'
```
=== "Python (requests)"
```python
import requests
import json
API_BASE_URL = "https://api.swarms.world"
API_KEY = "your_api_key_here"
headers = {
"x-api-key": API_KEY,
"Content-Type": "application/json"
}
swarm_config = {
"name": "Product Strategy Discussion",
"description": "Collaborative chat to develop product strategy",
"swarm_type": "GroupChat",
"task": "Discuss and develop a go-to-market strategy for a new AI-powered productivity tool targeting small businesses",
"agents": [
{
"agent_name": "Product Manager",
"description": "Leads product strategy and development",
"system_prompt": "You are a senior product manager. Focus on product positioning, features, user needs, and market fit. Ask probing questions and build on others ideas.",
"model_name": "gpt-4o",
"max_loops": 3,
},
{
"agent_name": "Marketing Strategist",
"description": "Develops marketing and positioning strategy",
"system_prompt": "You are a marketing strategist. Focus on target audience, messaging, channels, and competitive positioning. Contribute marketing insights to the discussion.",
"model_name": "gpt-4o",
"max_loops": 3,
},
{
"agent_name": "Sales Director",
"description": "Provides sales and customer perspective",
"system_prompt": "You are a sales director with small business experience. Focus on pricing, sales process, customer objections, and market adoption. Share practical sales insights.",
"model_name": "gpt-4o",
"max_loops": 3,
},
{
"agent_name": "UX Researcher",
"description": "Represents user experience and research insights",
"system_prompt": "You are a UX researcher specializing in small business tools. Focus on user behavior, usability, adoption barriers, and design considerations.",
"description": "Collaborative chat to develop product strategy",
"swarm_type": "GroupChat",
"output": "User: \n\nSystem: \n Group Chat Name: Product Strategy Discussion\nGroup Chat Description: Collaborative chat to develop product strategy\n Agents in your Group Chat: Available Agents for Team: None\n\n\n\n[Agent 1]\nName: Product Manager\nDescription: Leads product strategy and development\nRole.....",
@ -8,10 +8,12 @@ Each multi-agent architecture type is designed for specific use cases and can be
| MixtureOfAgents | Builds diverse teams of specialized agents, each contributing unique skills to solve complex problems. Excels at tasks requiring multiple types of expertise. | [Learn More](mixture_of_agents.md) |
| SequentialWorkflow | Executes tasks in a strict, predefined order. Perfect for workflows where each step depends on the completion of the previous one. | [Learn More](sequential_workflow.md) |
| ConcurrentWorkflow | Runs independent tasks in parallel, significantly reducing processing time for complex operations. Ideal for tasks that can be processed simultaneously. | [Learn More](concurrent_workflow.md) |
| GroupChat | Enables dynamic collaboration between agents through a chat-based interface, facilitating real-time information sharing and decision-making. | [Learn More](group_chat.md) |
| MultiAgentRouter | Acts as an intelligent task dispatcher, distributing work across agents based on their capabilities and current workload. | [Learn More](multi_agent_router.md) |
| MajorityVoting | Implements robust decision-making through consensus, ideal for tasks requiring collective intelligence or verification. | [Learn More](majority_voting.md) |
<!-- | SpreadSheetSwarm | Provides a structured approach to data management and operations, ideal for tasks involving data analysis, transformation, and systematic processing in a spreadsheet-like structure. | [Learn More](spreadsheet_swarm.md) | -->
<!-- | GroupChat | Enables dynamic collaboration between agents through a chat-based interface, facilitating real-time information sharing and decision-making. | [Learn More](group_chat.md) | -->
<!-- | AutoSwarmBuilder | Automatically configures agent architectures based on task requirements and performance metrics, simplifying swarm creation. | [Learn More](auto_swarm_builder.md) |
| HierarchicalSwarm | Implements a structured, multi-level approach to task management, with clear lines of authority and delegation. | [Learn More](hierarchical_swarm.md) | -->
<!-- | Auto | Intelligently selects the most effective swarm architecture for a given task based on context. | [Learn More](auto.md) | -->
harshalmore31
1 month ago