diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml index 729dd70c..0fad0e31 100644 --- a/docs/mkdocs.yml +++ b/docs/mkdocs.yml @@ -449,16 +449,14 @@ nav: - Swarm Types: - AgentRearrange: "swarms_cloud/agent_rearrange.md" - MixtureOfAgents: "swarms_cloud/mixture_of_agents.md" - # - SpreadSheetSwarm: "swarms_cloud/spreadsheet_swarm.md" - SequentialWorkflow: "swarms_cloud/sequential_workflow.md" - ConcurrentWorkflow: "swarms_cloud/concurrent_workflow.md" - GroupChat: "swarms_cloud/group_chat.md" - MultiAgentRouter: "swarms_cloud/multi_agent_router.md" + - HierarchicalSwarm: "swarms_cloud/hierarchical_swarm.md" + - MajorityVoting: "swarms_cloud/majority_voting.md" # - AutoSwarmBuilder: "swarms_cloud/auto_swarm_builder.md" - # - HierarchicalSwarm: "swarms_cloud/hierarchical_swarm.md" # - Auto: "swarms_cloud/auto.md" - - MajorityVoting: "swarms_cloud/majority_voting.md" - # - MALT: "swarms_cloud/malt.md" - Examples: - Medical Swarm: "swarms/examples/swarms_api_medical.md" - Finance Swarm: "swarms/examples/swarms_api_finance.md" diff --git a/docs/swarms_cloud/hierarchical_swarm.md b/docs/swarms_cloud/hierarchical_swarm.md index f65c7a46..70c8792e 100644 --- a/docs/swarms_cloud/hierarchical_swarm.md +++ b/docs/swarms_cloud/hierarchical_swarm.md @@ -1,12 +1,12 @@ -# HierarchicalSwarm +# HiearchicalSwarm *Implements structured, multi-level task management with clear authority* -**Swarm Type**: `HierarchicalSwarm` +**Swarm Type**: `HiearchicalSwarm` ## Overview -The HierarchicalSwarm implements a structured, multi-level approach to task management with clear lines of authority and delegation. This architecture organizes agents in a hierarchical structure where manager agents coordinate and oversee worker agents, enabling efficient task distribution and quality control. +The HiearchicalSwarm implements a structured, multi-level approach to task management with clear lines of authority and delegation. This architecture organizes agents in a hierarchical structure where manager agents coordinate and oversee worker agents, enabling efficient task distribution and quality control. Key features: - **Structured Hierarchy**: Clear organizational structure with managers and workers @@ -23,6 +23,212 @@ Key features: ## API Usage +### Basic HiearchicalSwarm Example + +=== "Shell (curl)" + ```bash + 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 ", + "description": "Parallel market research across different sectors", + "swarm_type": "HiearchicalSwarm", + "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-4o", + "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-4o", + "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-4o", + "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-4o", + "max_loops": 1, + "temperature": 0.3 + } + ], + "max_loops": 1 + }' + ``` + +=== "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": "Market Research ", + "description": "Parallel market research across different sectors", + "swarm_type": "HiearchicalSwarm", + "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-4o", + "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-4o", + "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-4o", + "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-4o", + "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("HiearchicalSwarm completed successfully!") + print(f"Cost: ${result['metadata']['billing_info']['total_cost']}") + print(f"Execution time: {result['metadata']['execution_time_seconds']} seconds") + print(f"Project plan: {result['output']}") + else: + print(f"Error: {response.status_code} - {response.text}") + ``` + +**Example Response**: +```json +{ + "job_id": "swarms-JIrcIAfs2d75xrXGaAL94uWyYJ8V", + "status": "success", + "swarm_name": "Market Research Auto", + "description": "Parallel market research across different sectors", + "swarm_type": "HiearchicalSwarm", + "output": [ + { + "role": "System", + "content": "These are the agents in your team. Each agent has a specific role and expertise to contribute to the team's objectives.\nTotal Agents: 4\n\nBelow is a summary of your team members and their primary responsibilities:\n| Agent Name | Description |\n|------------|-------------|\n| AI Market Analyst | Analyzes AI market trends and opportunities |\n| Healthcare Market Analyst | Analyzes healthcare market trends |\n| Fintech Market Analyst | Analyzes fintech market opportunities |\n| E-commerce Market Analyst | Analyzes e-commerce market trends |\n\nEach agent is designed to handle tasks within their area of expertise. Collaborate effectively by assigning tasks according to these roles." + }, + { + "role": "Director", + "content": [ + { + "role": "Director", + "content": [ + { + "function": { + "arguments": "{\"plan\":\"Conduct a comprehensive analysis of market opportunities in the AI, healthcare, fintech, and e-commerce sectors. Each market analyst will focus on their respective sector, gathering data on current trends, growth opportunities, and potential challenges. The findings will be compiled into a report for strategic decision-making.\",\"orders\":[{\"agent_name\":\"AI Market Analyst\",\"task\":\"Research current trends in the AI market, identify growth opportunities, and analyze potential challenges.\"},{\"agent_name\":\"Healthcare Market Analyst\",\"task\":\"Analyze the healthcare market for emerging trends, growth opportunities, and possible challenges.\"},{\"agent_name\":\"Fintech Market Analyst\",\"task\":\"Investigate the fintech sector for current trends, identify opportunities for growth, and assess challenges.\"},{\"agent_name\":\"E-commerce Market Analyst\",\"task\":\"Examine e-commerce market trends, identify growth opportunities, and analyze potential challenges.\"}]}", + "name": "ModelMetaclass" + }, + "id": "call_GxiyzIRb2oGQXokbbkeaeVry", + "type": "function" + } + ] + } + ] + }, + { + "role": "AI Market Analyst", + "content": "### AI Market Analysis: Trends, Opportunities, and Challenges\n\n#### Current Trends in the AI Market:\n\n1. **Increased Adoption Across Industries**..." + }, + { + "role": "Healthcare Market Analyst", + "content": "### Healthcare Market Analysis: Trends, Opportunities, and Challenges\n\n#### Current Trends in the Healthcare Market:\n\n1. **Telehealth Expansion**..." + }, + { + "role": "Fintech Market Analyst", + "content": "### Fintech Market Analysis: Trends, Opportunities, and Challenges\n\n#### Current Trends in the Fintech Market:\n\n1. **Digital Payments Proliferation**...." + }, + { + "role": "E-commerce Market Analyst", + "content": "### E-commerce Market Analysis: Trends, Opportunities, and Challenges\n\n#### Current Trends in the E-commerce Market:\n\n1. **Omnichannel Retailing**...." + }, + { + "role": "Director", + "content": "### Feedback for Worker Agents\n\n#### AI Market Analyst\n\n**Strengths:**\n- Comprehensive coverage of current trends, growth opportunities, and challenges in the AI market.\n- Clear categorization of insights, making it easy to follow and understand.\n\n**Weaknesses....." + }, + { + "role": "System", + "content": "--- Loop 1/1 completed ---" + } + ], + "number_of_agents": 4, + "service_tier": "standard", + "execution_time": 94.07934331893921, + "usage": { + "input_tokens": 35, + "output_tokens": 3827, + "total_tokens": 3862, + "billing_info": { + "cost_breakdown": { + "agent_cost": 0.04, + "input_token_cost": 0.000105, + "output_token_cost": 0.057405, + "token_counts": { + "total_input_tokens": 35, + "total_output_tokens": 3827, + "total_tokens": 3862 + }, + "num_agents": 4, + "service_tier": "standard", + "night_time_discount_applied": false + }, + "total_cost": 0.09751, + "discount_active": false, + "discount_type": "none", + "discount_percentage": 0 + } + } +} +``` ## Configuration Options diff --git a/docs/swarms_cloud/malt.md b/docs/swarms_cloud/malt.md deleted file mode 100644 index 3247e854..00000000 --- a/docs/swarms_cloud/malt.md +++ /dev/null @@ -1,40 +0,0 @@ -# MALT - -*Specialized framework for complex language-based tasks and processing* - -**Swarm Type**: `MALT` - -## Overview - -MALT (Multi-Agent Language Task) is a specialized framework optimized for complex language-based tasks, optimizing agent collaboration for sophisticated language processing operations. This architecture excels at tasks requiring deep linguistic analysis, natural language understanding, and complex text generation workflows. - -Key features: -- **Language Optimization**: Specifically designed for natural language tasks -- **Linguistic Collaboration**: Agents work together on complex language operations -- **Text Processing Pipeline**: Structured approach to language task workflows -- **Advanced NLP**: Optimized for sophisticated language understanding tasks - -## Use Cases - -- Complex document analysis and processing -- Multi-language translation and localization -- Advanced content generation and editing -- Linguistic research and analysis tasks - -## API Usage - - -``` - -## Best Practices - -- Use MALT for sophisticated language processing tasks -- Design agents with complementary linguistic analysis capabilities -- Ideal for tasks requiring deep language understanding -- Consider multiple levels of linguistic analysis (syntax, semantics, pragmatics) - -## Related Swarm Types - -- [SequentialWorkflow](sequential_workflow.md) - For ordered language processing -- [MixtureOfAgents](mixture_of_agents.md) - For diverse linguistic expertise -- [HierarchicalSwarm](hierarchical_swarm.md) - For structured language analysis \ No newline at end of file diff --git a/docs/swarms_cloud/spreadsheet_swarm.md b/docs/swarms_cloud/spreadsheet_swarm.md deleted file mode 100644 index 47beafaf..00000000 --- a/docs/swarms_cloud/spreadsheet_swarm.md +++ /dev/null @@ -1,41 +0,0 @@ -# SpreadSheetSwarm - -*Structured approach to data management and operations in spreadsheet-like format* - -**Swarm Type**: `SpreadSheetSwarm` - -## Overview - -The 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. This architecture organizes agents to work on data in a tabular format with clear rows, columns, and processing workflows. - -Key features: -- **Structured Data Processing**: Organizes work in spreadsheet-like rows and columns -- **Systematic Operations**: Sequential and methodical data handling -- **Data Transformation**: Efficient processing of structured datasets -- **Collaborative Analysis**: Multiple agents working on different data aspects - -## Use Cases - -- Financial data analysis and reporting -- Customer data processing and segmentation -- Inventory management and tracking -- Research data compilation and analysis - -## API Usage - -### Basic SpreadSheetSwarm Example - - - -## Best Practices - -- Structure data in clear, logical formats before processing -- Use systematic, step-by-step analysis approaches -- Ideal for quantitative analysis and reporting tasks -- Ensure data validation before proceeding with analysis - -## Related Swarm Types - -- [SequentialWorkflow](sequential_workflow.md) - For ordered data processing -- [ConcurrentWorkflow](concurrent_workflow.md) - For parallel data analysis -- [HierarchicalSwarm](hierarchical_swarm.md) - For complex data projects \ No newline at end of file diff --git a/docs/swarms_cloud/swarm_types.md b/docs/swarms_cloud/swarm_types.md index d964ce0c..5773237b 100644 --- a/docs/swarms_cloud/swarm_types.md +++ b/docs/swarms_cloud/swarm_types.md @@ -9,15 +9,14 @@ Each multi-agent architecture type is designed for specific use cases and can be | 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) | +| HierarchicalSwarm | Implements a structured, multi-level approach to task management, with clear lines of authority and delegation. | [Learn More](hierarchical_swarm.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) | - - + # Learn More