# tests/conftest.py
import pytest
import os
from unittest.mock import Mock, patch
from praisonaiagents import Agent, Task

# Test configuration
@pytest.fixture(scope="session")
def test_config():
    return {
        "use_mock_llm": os.getenv("USE_MOCK_LLM", "true").lower() == "true",
        "test_api_key": "test-key-123",
        "max_test_duration": 30,  # seconds
        "mock_response_delay": 0.1  # simulate API delay
    }

# Mock LLM for testing
@pytest.fixture
def mock_llm(test_config):
    if not test_config["use_mock_llm"]:
        return None
    
    mock = Mock()
    mock.generate.return_value = "Mocked response"
    mock.agenerate.return_value = "Mocked async response"
    return mock

# Test agent fixture
@pytest.fixture
def test_agent(mock_llm):
    agent = Agent(
        name="TestAgent",
        instructions="You are a test agent",
        llm=mock_llm
    )
    return agent

# tests/utils.py
import asyncio
import time
from typing import Any, Callable, Optional
from contextlib import contextmanager

class TestMetrics:
    def __init__(self):
        self.execution_times = []
        self.token_usage = []
        self.error_count = 0
    
    def record_execution(self, duration: float, tokens: int = 0):
        self.execution_times.append(duration)
        self.token_usage.append(tokens)
    
    def record_error(self):
        self.error_count += 1
    
    def get_stats(self):
        return {
            "avg_execution_time": sum(self.execution_times) / len(self.execution_times) if self.execution_times else 0,
            "total_tokens": sum(self.token_usage),
            "error_rate": self.error_count / (len(self.execution_times) + self.error_count) if self.execution_times else 0
        }

@contextmanager
def measure_performance():
    """Context manager to measure execution time"""
    start = time.time()
    yield
    duration = time.time() - start
    return duration

def async_test(coro):
    """Decorator to run async tests"""
    def wrapper(*args, **kwargs):
        loop = asyncio.get_event_loop()
        return loop.run_until_complete(coro(*args, **kwargs))
    return wrapper

# tests/unit/test_agent.py
import pytest
from unittest.mock import Mock, patch, AsyncMock
from praisonaiagents import Agent

class TestAgent:
    def test_agent_initialization(self):
        """Test agent can be initialized with basic parameters"""
        agent = Agent(
            name="TestAgent",
            instructions="Test instructions",
            llm_model="gpt-4"
        )
        
        assert agent.name == "TestAgent"
        assert agent.instructions == "Test instructions"
        assert agent.llm_model == "gpt-4"
    
    def test_agent_with_tools(self):
        """Test agent initialization with tools"""
        mock_tool = Mock()
        mock_tool.name = "test_tool"
        
        agent = Agent(
            name="ToolAgent",
            instructions="Agent with tools",
            tools=[mock_tool]
        )
        
        assert len(agent.tools) == 1
        assert agent.tools[0].name == "test_tool"
    
    @patch('praisonaiagents.agent.agent.litellm.completion')
    def test_agent_run_sync(self, mock_completion):
        """Test synchronous agent execution"""
        # Setup mock response
        mock_completion.return_value = Mock(
            choices=[Mock(message=Mock(content="Test response"))]
        )
        
        agent = Agent(name="TestAgent", instructions="Test")
        result = agent.run("Test input")
        
        assert result == "Test response"
        mock_completion.assert_called_once()
    
    @patch('praisonaiagents.agent.agent.litellm.acompletion')
    async def test_agent_run_async(self, mock_acompletion):
        """Test asynchronous agent execution"""
        # Setup mock response
        mock_acompletion.return_value = Mock(
            choices=[Mock(message=Mock(content="Async test response"))]
        )
        
        agent = Agent(name="TestAgent", instructions="Test")
        result = await agent.arun("Test input")
        
        assert result == "Async test response"
        mock_acompletion.assert_called_once()
    
    def test_agent_validation(self):
        """Test agent input validation"""
        with pytest.raises(ValueError):
            Agent(name="", instructions="Test")  # Empty name
        
        with pytest.raises(ValueError):
            Agent(name="Test", instructions="")  # Empty instructions
        
        with pytest.raises(ValueError):
            Agent(name="Test", instructions="Test", max_tokens=-1)  # Invalid max_tokens

# tests/unit/test_task.py
import pytest
from unittest.mock import Mock
from praisonaiagents import Task, Agent

class TestTask:
    def test_task_creation(self):
        """Test task initialization"""
        agent = Mock(spec=Agent)
        task = Task(
            description="Test task",
            agent=agent,
            expected_output="Expected result"
        )
        
        assert task.description == "Test task"
        assert task.agent == agent
        assert task.expected_output == "Expected result"
    
    def test_task_dependencies(self):
        """Test task with dependencies"""
        agent = Mock(spec=Agent)
        task1 = Task(description="Task 1", agent=agent)
        task2 = Task(description="Task 2", agent=agent, depends_on=[task1])
        
        assert len(task2.depends_on) == 1
        assert task2.depends_on[0] == task1
    
    def test_task_context(self):
        """Test task context passing"""
        agent = Mock(spec=Agent)
        context = {"key": "value"}
        
        task = Task(
            description="Test task",
            agent=agent,
            context=context
        )
        
        assert task.context == context
    
    @patch('praisonaiagents.task.task.Task.execute')
    def test_task_execution(self, mock_execute):
        """Test task execution"""
        mock_execute.return_value = "Task completed"
        
        agent = Mock(spec=Agent)
        task = Task(description="Test", agent=agent)
        result = task.execute()
        
        assert result == "Task completed"
        mock_execute.assert_called_once()

# tests/unit/test_tools.py
import pytest
from unittest.mock import Mock, patch
from praisonaiagents import Tool

class TestTools:
    def test_tool_creation(self):
        """Test tool initialization"""
        def sample_function(x: int) -> int:
            return x * 2
        
        tool = Tool(
            name="multiplier",
            description="Multiplies input by 2",
            function=sample_function
        )
        
        assert tool.name == "multiplier"
        assert tool.function(5) == 10
    
    def test_tool_validation(self):
        """Test tool parameter validation"""
        def typed_function(x: int, y: str) -> str:
            return f"{y}: {x}"
        
        tool = Tool(
            name="typed_tool",
            description="Tool with type hints",
            function=typed_function
        )
        
        # Should work with correct types
        result = tool.execute(x=5, y="Number")
        assert result == "Number: 5"
        
        # Should handle type conversion
        result = tool.execute(x="5", y=10)
        assert result == "10: 5"
    
    def test_async_tool(self):
        """Test asynchronous tool"""
        async def async_function(x: int) -> int:
            return x * 3
        
        tool = Tool(
            name="async_multiplier",
            description="Async multiplier",
            function=async_function
        )
        
        assert tool.is_async
        # Test execution would require async context

# tests/integration/test_multi_agent.py
import pytest
from praisonaiagents import Agent, Task, PraisonAIAgents

class TestMultiAgentIntegration:
    @pytest.mark.integration
    def test_agent_collaboration(self, mock_llm):
        """Test multiple agents working together"""
        researcher = Agent(
            name="Researcher",
            instructions="Research the topic",
            llm=mock_llm
        )
        
        writer = Agent(
            name="Writer",
            instructions="Write based on research",
            llm=mock_llm
        )
        
        # Create tasks
        research_task = Task(
            description="Research AI trends",
            agent=researcher,
            expected_output="Research findings"
        )
        
        writing_task = Task(
            description="Write article on AI trends",
            agent=writer,
            depends_on=[research_task],
            expected_output="Article"
        )
        
        # Create workflow
        workflow = PraisonAIAgents(
            agents=[researcher, writer],
            tasks=[research_task, writing_task]
        )
        
        # Execute workflow
        result = workflow.start()
        
        assert result is not None
        assert len(workflow.results) == 2
    
    @pytest.mark.integration
    async def test_async_agent_workflow(self, mock_llm):
        """Test asynchronous multi-agent workflow"""
        agents = [
            Agent(name=f"Agent{i}", instructions=f"Process part {i}", llm=mock_llm)
            for i in range(3)
        ]
        
        tasks = [
            Task(description=f"Task {i}", agent=agents[i])
            for i in range(3)
        ]
        
        workflow = PraisonAIAgents(agents=agents, tasks=tasks)
        results = await workflow.astart()
        
        assert len(results) == 3

# tests/integration/test_tool_integration.py
import pytest
from unittest.mock import Mock, patch
import aiohttp
from praisonaiagents import Agent, Tool

class TestToolIntegration:
    @pytest.mark.integration
    @patch('aiohttp.ClientSession.get')
    async def test_web_search_tool(self, mock_get):
        """Test web search tool integration"""
        # Mock API response
        mock_response = Mock()
        mock_response.json = Mock(return_value={
            "results": [{"title": "Test", "snippet": "Test result"}]
        })
        mock_get.return_value.__aenter__.return_value = mock_response
        
        # Create search tool
        async def web_search(query: str) -> str:
            async with aiohttp.ClientSession() as session:
                async with session.get(f"https://api.search.com?q={query}") as response:
                    data = await response.json()
                    return data["results"][0]["snippet"]
        
        search_tool = Tool(
            name="web_search",
            description="Search the web",
            function=web_search
        )
        
        # Test with agent
        agent = Agent(
            name="SearchAgent",
            instructions="Search for information",
            tools=[search_tool]
        )
        
        result = await agent.arun("Search for test")
        assert "Test result" in str(result)
    
    @pytest.mark.integration
    def test_tool_error_handling(self):
        """Test tool error handling"""
        def failing_tool(x: int) -> int:
            raise ValueError("Tool failed")
        
        tool = Tool(
            name="failing_tool",
            description="Tool that fails",
            function=failing_tool
        )
        
        agent = Agent(
            name="TestAgent",
            instructions="Use the tool",
            tools=[tool]
        )
        
        # Agent should handle tool failure gracefully
        with pytest.raises(Exception):
            agent.run("Use failing_tool with x=5")

# tests/performance/test_load.py
import pytest
import asyncio
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from praisonaiagents import Agent

class TestPerformance:
    @pytest.mark.performance
    def test_concurrent_agents(self, test_agent):
        """Test multiple agents running concurrently"""
        num_agents = 10
        num_requests = 5
        
        def run_agent(agent_id):
            agent = Agent(
                name=f"Agent{agent_id}",
                instructions="Process request"
            )
            results = []
            for i in range(num_requests):
                start = time.time()
                result = agent.run(f"Request {i}")
                duration = time.time() - start
                results.append(duration)
            return results
        
        with ThreadPoolExecutor(max_workers=num_agents) as executor:
            futures = [executor.submit(run_agent, i) for i in range(num_agents)]
            all_results = []
            
            for future in as_completed(futures):
                all_results.extend(future.result())
        
        avg_time = sum(all_results) / len(all_results)
        assert avg_time < 5  # Average response time under 5 seconds
    
    @pytest.mark.performance
    async def test_async_performance(self):
        """Test async agent performance"""
        num_concurrent = 20
        
        async def process_request(agent, request_id):
            start = time.time()
            await agent.arun(f"Process request {request_id}")
            return time.time() - start
        
        agent = Agent(name="AsyncAgent", instructions="Process quickly")
        
        tasks = [
            process_request(agent, i)
            for i in range(num_concurrent)
        ]
        
        results = await asyncio.gather(*tasks)
        
        avg_time = sum(results) / len(results)
        max_time = max(results)
        
        assert avg_time < 3  # Average under 3 seconds
        assert max_time < 10  # No request over 10 seconds

# tests/performance/test_memory.py
import pytest
import psutil
import gc
from praisonaiagents import Agent, Memory

class TestMemoryUsage:
    @pytest.mark.performance
    def test_memory_leak(self):
        """Test for memory leaks in agent execution"""
        process = psutil.Process()
        initial_memory = process.memory_info().rss / 1024 / 1024  # MB
        
        # Run many agent iterations
        agent = Agent(name="MemTestAgent", instructions="Test memory")
        for i in range(100):
            agent.run(f"Iteration {i}")
            if i % 10 == 0:
                gc.collect()
        
        final_memory = process.memory_info().rss / 1024 / 1024  # MB
        memory_increase = final_memory - initial_memory
        
        # Memory increase should be reasonable
        assert memory_increase < 100  # Less than 100MB increase
    
    @pytest.mark.performance
    def test_conversation_memory_limit(self):
        """Test conversation memory limits"""
        agent = Agent(
            name="MemoryAgent",
            instructions="Remember conversations",
            memory=Memory(max_messages=10)
        )
        
        # Add many messages
        for i in range(20):
            agent.run(f"Message {i}")
        
        # Check memory is limited
        assert len(agent.memory.messages) <= 10

# tests/mocks/llm_mock.py
from typing import Dict, List, Any
import random
import time

class MockLLM:
    def __init__(self, responses: Dict[str, str] = None):
        self.responses = responses or {}
        self.default_responses = [
            "I understand your request.",
            "Here's what I found.",
            "Task completed successfully.",
            "Processing your request."
        ]
        self.call_count = 0
        self.last_prompt = None
    
    def generate(self, prompt: str, **kwargs) -> str:
        self.call_count += 1
        self.last_prompt = prompt
        
        # Simulate processing time
        time.sleep(0.1)
        
        # Check for specific responses
        for key, response in self.responses.items():
            if key in prompt.lower():
                return response
        
        # Return random default response
        return random.choice(self.default_responses)
    
    async def agenerate(self, prompt: str, **kwargs) -> str:
        await asyncio.sleep(0.1)
        return self.generate(prompt, **kwargs)

# Usage in tests
@pytest.fixture
def smart_mock_llm():
    return MockLLM(responses={
        "weather": "It's sunny today with a temperature of 72°F.",
        "calculate": "The result is 42.",
        "error": "Error: Invalid input provided."
    })

# tests/mocks/tool_mock.py
class MockTool:
    def __init__(self, name: str, return_value: Any = None, side_effect: Any = None):
        self.name = name
        self.return_value = return_value
        self.side_effect = side_effect
        self.call_count = 0
        self.call_args_list = []
    
    def execute(self, **kwargs):
        self.call_count += 1
        self.call_args_list.append(kwargs)
        
        if self.side_effect:
            if isinstance(self.side_effect, Exception):
                raise self.side_effect
            return self.side_effect(**kwargs)
        
        return self.return_value or f"Mock result from {self.name}"

# Usage
mock_search = MockTool(
    name="search",
    return_value="Search results for your query"
)

mock_calculator = MockTool(
    name="calculator",
    side_effect=lambda expression: eval(expression)
)

# tests/factories.py
from dataclasses import dataclass
from typing import List, Optional
import factory
from faker import Faker

fake = Faker()

@dataclass
class TestScenario:
    name: str
    input: str
    expected_output: str
    agent_instructions: str
    tools: List[str] = None

class ScenarioFactory(factory.Factory):
    class Meta:
        model = TestScenario
    
    name = factory.LazyFunction(lambda: f"Scenario_{fake.word()}")
    input = factory.LazyFunction(fake.sentence)
    expected_output = factory.LazyFunction(fake.paragraph)
    agent_instructions = factory.LazyFunction(
        lambda: f"You are a {fake.job()} assistant"
    )
    tools = factory.LazyFunction(
        lambda: [fake.word() for _ in range(random.randint(0, 3))]
    )

# Usage
test_scenarios = [ScenarioFactory() for _ in range(10)]

# tests/data/test_cases.py
TEST_CASES = {
    "simple_queries": [
        ("What is 2+2?", "4"),
        ("Hello", "Hello! How can I help you?"),
        ("Goodbye", "Goodbye! Have a great day!")
    ],
    "complex_queries": [
        (
            "Analyze the sentiment of: This product is amazing!",
            "positive"
        ),
        (
            "Summarize: Long text here...",
            "Summary of the text"
        )
    ],
    "edge_cases": [
        ("", "I didn't receive any input."),
        ("🤖" * 100, "I see you've sent many robot emojis."),
        (None, "Invalid input received.")
    ]
}

# .github/workflows/test.yml
name: Test Suite

on:
  push:
    branches: [ main, develop ]
  pull_request:
    branches: [ main ]

jobs:
  test:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: [3.8, 3.9, 3.10, 3.11]
    
    steps:
    - uses: actions/checkout@v3
    
    - name: Set up Python
      uses: actions/setup-python@v4
      with:
        python-version: ${{ matrix.python-version }}
    
    - name: Cache dependencies
      uses: actions/cache@v3
      with:
        path: ~/.cache/pip
        key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
    
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
        pip install -r requirements-test.txt
    
    - name: Run unit tests
      run: |
        pytest tests/unit -v --cov=praisonaiagents --cov-report=xml
      env:
        USE_MOCK_LLM: true
    
    - name: Run integration tests
      run: |
        pytest tests/integration -v -m integration
      env:
        USE_MOCK_LLM: true
    
    - name: Run performance tests
      run: |
        pytest tests/performance -v -m performance
      if: github.event_name == 'push'
    
    - name: Upload coverage
      uses: codecov/codecov-action@v3
      with:
        file: ./coverage.xml

# tests/pytest.ini
[pytest]
minversion = 6.0
addopts = 
    -ra 
    -q 
    --strict-markers
    --cov=praisonaiagents
    --cov-report=html
    --cov-report=term-missing
    --maxfail=1
    --tb=short
    --benchmark-disable

markers =
    unit: Unit tests
    integration: Integration tests
    performance: Performance tests
    slow: Slow tests
    flaky: Flaky tests that may fail occasionally

testpaths = tests

# Coverage settings
[coverage:run]
source = praisonaiagents
omit = 
    */tests/*
    */migrations/*
    */__pycache__/*

[coverage:report]
precision = 2
show_missing = True
skip_covered = False

# Good test names
def test_agent_should_return_error_when_invalid_input():
    pass

def test_task_execution_with_dependencies_completes_in_order():
    pass

def test_memory_clears_old_messages_when_limit_exceeded():
    pass

# Bad test names
def test_agent():  # Too vague
    pass

def test_1():  # Not descriptive
    pass

tests/
├── conftest.py          # Shared fixtures
├── unit/                # Unit tests
│   ├── test_agent.py
│   ├── test_task.py
│   └── test_tools.py
├── integration/         # Integration tests
│   ├── test_workflows.py
│   └── test_multi_agent.py
├── performance/         # Performance tests
│   └── test_load.py
├── e2e/                 # End-to-end tests
│   └── test_scenarios.py
├── mocks/              # Mock implementations
│   └── llm_mock.py
└── data/               # Test data
    └── test_cases.py

@pytest.mark.parametrize("input,expected", [
    ("Hello", "Hi there!"),
    ("How are you?", "I'm doing well!"),
    ("Goodbye", "See you later!"),
])
def test_agent_responses(test_agent, input, expected):
    result = test_agent.run(input)
    assert expected in result

# tests/test_snapshots.py
import pytest
from syrupy import snapshot

def test_agent_output_snapshot(test_agent, snapshot):
    result = test_agent.run("Generate a report")
    assert result == snapshot

# tests/test_properties.py
from hypothesis import given, strategies as st

@given(st.text(min_size=1, max_size=1000))
def test_agent_handles_any_text_input(test_agent, text):
    result = test_agent.run(text)
    assert result is not None
    assert isinstance(result, str)
    assert len(result) > 0

# tests/debug_utils.py
import json
import pdb
from rich import print as rprint
from rich.table import Table

def debug_agent_state(agent):
    """Print agent state for debugging"""
    table = Table(title=f"Agent: {agent.name}")
    table.add_column("Property", style="cyan")
    table.add_column("Value", style="green")
    
    table.add_row("Instructions", agent.instructions[:50] + "...")
    table.add_row("Tools", str(len(agent.tools)))
    table.add_row("Memory Size", str(len(agent.memory.messages)))
    table.add_row("Model", agent.llm_model)
    
    rprint(table)

def trace_execution(func):
    """Decorator to trace function execution"""
    def wrapper(*args, **kwargs):
        print(f"Entering {func.__name__}")
        pdb.set_trace()
        result = func(*args, **kwargs)
        print(f"Exiting {func.__name__} with result: {result}")
        return result
    return wrapper

# Enable detailed logging for failed tests
def test_complex_workflow():
    import logging
    logging.basicConfig(level=logging.DEBUG)
    
    # Your test code here
    
# Use pytest debugging
# Run with: pytest -vv --pdb --pdbcls=IPython.terminal.debugger:Pdb

# Capture stdout/stderr
def test_with_output(capsys):
    agent.run("test")
    captured = capsys.readouterr()
    print(f"Stdout: {captured.out}")
    print(f"Stderr: {captured.err}")