swarms/tests

Swarms Test Suite

This directory contains comprehensive tests for the Swarms framework, covering all major components including agents, workflows, tools, utilities, and more.

📁 Directory Structure

Core Test Files

• test_comprehensive_test.py - Main comprehensive test suite that runs all major Swarms components
• test___init__.py - Package initialization tests
• requirements.txt - Test dependencies (swarms, pytest, matplotlib, loguru)

Test Categories

🤖 Agent Tests (/agent/)

Tests for individual agent functionality and behavior:

/agents/ - Core agent functionality

• test_agent_logging.py - Agent logging and monitoring capabilities
• test_create_agents_from_yaml.py - YAML-based agent creation
• test_litellm_args_kwargs.py - LiteLLM argument handling
• test_llm_args.py - LLM argument processing
• test_llm_handling_args.py - LLM argument management
• test_tool_agent.py - Tool-enabled agent functionality

/benchmark_agent/ - Agent performance and benchmarking

• test_agent_benchmark_init.py - Agent benchmark initialization
• test_agent_exec_benchmark.py - Agent execution benchmarking
• test_auto_test_eval.py - Automated test evaluation
• test_github_summarizer_agent.py - GitHub summarization agent
• test_profiling_agent.py - Agent performance profiling

🏗️ Structure Tests (/structs/)

Tests for Swarms structural components and workflows:

• test_agent.py - Core Agent class functionality
• test_agent_features.py - Agent feature testing
• test_agent_rearrange.py - Agent rearrangement capabilities
• test_agentrearrange.py - Alternative agent rearrangement tests
• test_airflow_swarm.py - Airflow integration
• test_auto_swarm_builder_fix.py - Auto swarm builder fixes
• test_auto_swarms_builder.py - Automated swarm construction
• test_base_workflow.py - Base workflow functionality
• test_base.py - Base class implementations
• test_board_of_directors_swarm.py - Board of directors swarm pattern
• test_concurrent_workflow.py - Concurrent workflow execution
• test_conversation.py - Conversation management
• test_forest_swarm.py - Forest swarm architecture
• test_graph_workflow_comprehensive.py - Graph-based workflows
• test_groupchat.py - Group chat functionality
• test_majority_voting.py - Majority voting mechanisms
• test_moa.py - Mixture of Agents (MoA) testing
• test_multi_agent_collab.py - Multi-agent collaboration
• test_multi_agent_orchestrator.py - Multi-agent orchestration
• test_reasoning_agent_router_all.py - Reasoning agent routing
• test_recursive_workflow.py - Recursive workflow patterns
• test_round_robin_swarm.py - Round-robin swarm scheduling
• test_sequential_workflow.py - Sequential workflow execution
• test_spreadsheet.py - Spreadsheet swarm functionality
• test_swarm_architectures.py - Various swarm architectures
• test_yaml_model.py - YAML model configuration

🔧 Tools Tests (/tools/)

Tests for tool integration and functionality:

• test_base_tool.py - Base tool class functionality
• test_output_str_fix.py - Output string formatting fixes
• test_parse_tools.py - Tool parsing and execution
• test_support_mcp.py - MCP (Model Context Protocol) support

🛠️ Utilities Tests (/utils/)

Tests for utility functions and helpers:

• test_acompletions.py - Async completion handling
• test_auto_check_download.py - Automatic download checking
• test_display_markdown_message.py - Markdown message display
• test_docstring_parser.py - Docstring parsing utilities
• test_extract_code_from_markdown.py - Code extraction from markdown
• test_formatter.py - Text formatting utilities
• test_litellm_wrapper.py - LiteLLM wrapper functionality
• test_math_eval.py - Mathematical expression evaluation
• test_md_output.py - Markdown output handling
• test_metrics_decorator.py - Metrics collection decorators
• test_pdf_to_text.py - PDF to text conversion
• test_try_except_wrapper.py - Error handling wrappers

🎨 Artifacts Tests (/artifacts/)

Tests for artifact management and versioning:

• test_artifact_main.py - Core artifact functionality
• test_artifact_output_types.py - Artifact output type handling

💬 Communication Tests (/communication/)

Tests for communication and conversation management:

• test_conversation.py - Conversation handling and persistence

📊 AOP (Aspect-Oriented Programming) Tests (/aop/)

Advanced testing with benchmarking and performance analysis:

• aop_benchmark.py - Comprehensive AOP benchmarking suite
• test_data/ - Benchmark data and results
  • aop_benchmark_data/ - Benchmark results and visualizations
  • image1.jpg, image2.png - Test images

📈 Telemetry Tests (/telemetry/)

Tests for telemetry and monitoring:

• test_user_utils.py - User utility telemetry

🚀 Running Tests

Prerequisites

Install test dependencies:

pip install -r requirements.txt

Running All Tests

pytest

Running Specific Test Categories

# Run agent tests
pytest agent/

# Run structure tests
pytest structs/

# Run utility tests
pytest utils/

# Run tool tests
pytest tools/

Running Individual Test Files

# Run comprehensive test suite
pytest test_comprehensive_test.py

# Run specific test file
pytest structs/test_agent.py

Running with Coverage

pytest --cov=swarms --cov-report=html

📋 Test Features

Comprehensive Testing

• Agent Functionality: Complete testing of agent creation, execution, and management
• Workflow Testing: Various workflow patterns including sequential, concurrent, and recursive
• Tool Integration: Testing of tool parsing, execution, and MCP support
• Performance Benchmarking: AOP benchmarking with multiple LLM providers
• Error Handling: Comprehensive error handling and recovery testing

Test Data

• Benchmark results with CSV and Excel exports
• Performance visualizations (PNG charts)
• Test images for multimodal testing
• Conversation cache files for persistence testing

Supported LLM Providers

The AOP benchmark tests support multiple LLM providers:

• OpenAI (GPT-4o, GPT-4o-mini, GPT-4-turbo)
• Anthropic (Claude 3.5 Sonnet, Claude 3 Haiku, Claude 3 Sonnet)
• Google (Gemini 1.5 Pro, Gemini 1.5 Flash)
• Meta (Llama 3.1 8B, Llama 3.1 70B)

🔧 Configuration

Environment Variables

Tests require the following environment variables:

• OPENAI_API_KEY - OpenAI API key for testing
• Additional API keys for other providers (optional)

Test Configuration

• Maximum agents: 20 (configurable in AOP benchmark)
• Requests per test: 20
• Concurrent requests: 5
• Timeout settings: Configurable per test type

📊 Benchmarking

The AOP benchmark suite provides:

• Performance metrics across multiple LLM providers
• Memory usage tracking
• Response time analysis
• Throughput measurements
• Visual performance reports

🐛 Debugging

Verbose Output

pytest -v

Debug Mode

pytest --pdb

Logging

Tests use Loguru for comprehensive logging. Check console output for detailed test execution logs.

📝 Contributing

When adding new tests:

1. Follow the existing directory structure
2. Use descriptive test names
3. Include proper docstrings
4. Add appropriate fixtures and mocks
5. Update this README if adding new test categories

🔍 Test Coverage

The test suite aims for comprehensive coverage of:

• ✅ Agent creation and execution
• ✅ Workflow patterns and orchestration
• ✅ Tool integration and execution
• ✅ Utility functions and helpers
• ✅ Error handling and edge cases
• ✅ Performance and benchmarking
• ✅ Communication and conversation management
• ✅ Artifact management and versioning