fixed HiearchicalSwarm & cleanups !

1 month ago · cf7357fd8e
parent 1444a719c4
commit cf7357fd8e
5 changed files with 213 additions and 91 deletions
--- 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"
--- 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
--- a/docs/swarms_cloud/malt.md
+++ b/docs/swarms_cloud/malt.md
@ -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
--- a/docs/swarms_cloud/spreadsheet_swarm.md
+++ b/docs/swarms_cloud/spreadsheet_swarm.md
@ -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
--- 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) |
 <!-- | 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) | -->
 <!-- | 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) | -->
-<!-- | MALT                | Specialized framework for language-based tasks, optimizing agent collaboration for complex language processing operations. | [Learn More](malt.md) | -->
+
 # Learn More