Add selective task execution feature for issue #2941

- Add tags field to Task class for categorization
- Add task_selector parameter to Crew class
- Implement task filtering in _execute_tasks method
- Add Process.selective type with validation
- Add helper method for tag-based selection
- Add comprehensive tests covering all scenarios
- Maintain backward compatibility with existing crews

Fixes #2941: Users can now run only specific agents/tasks based on input parameters like 'action', rather than executing the entire crew process.

Co-Authored-By: João <joao@crewai.com>

tests/test_selective_execution_example.py

@@ -0,0 +1,66 @@
+"""Example demonstrating selective execution for issue #2941."""
+
+import pytest
+from crewai import Agent, Crew, Task, Process
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_issue_2941_example():
+    """Reproduce and test the exact scenario from issue #2941."""
+    
+    holiday_agent = Agent(role="Holiday Researcher", goal="Research holidays", backstory="Expert in holidays")
+    macro_agent = Agent(role="Macro Analyst", goal="Analyze macro data", backstory="Expert in macroeconomics") 
+    news_agent = Agent(role="News Summarizer", goal="Summarize news", backstory="Expert in news analysis")
+    forecast_agent = Agent(role="Forecaster", goal="Create forecasts", backstory="Expert in forecasting")
+    query_agent = Agent(role="Query Handler", goal="Handle user queries", backstory="Expert in query processing")
+    
+    holiday_task = Task(description="Research holiday information", expected_output="Holiday data", agent=holiday_agent, tags=["holiday"])
+    macro_task = Task(description="Extract macroeconomic data", expected_output="Macro data", agent=macro_agent, tags=["macro"])  
+    news_task = Task(description="Summarize relevant news", expected_output="News summary", agent=news_agent, tags=["news"])
+    forecast_task = Task(description="Generate forecast", expected_output="Forecast result", agent=forecast_agent, tags=["forecast"])
+    query_task = Task(description="Handle user query", expected_output="Query response", agent=query_agent, tags=["query"])
+    
+    crew = Crew(
+        agents=[holiday_agent, macro_agent, news_agent, forecast_agent, query_agent],
+        tasks=[holiday_task, macro_task, news_task, forecast_task, query_task],
+        process=Process.selective,
+        task_selector=Crew.create_tag_selector()
+    )
+    
+    inputs = {
+        'data_file': 'sample.csv',
+        'action': 'forecast', 
+        'country_code': 'US',
+        'topic': 'Egg_prices',
+        'query': "Provide forecasted result on the input data"
+    }
+    
+    result = crew.kickoff(inputs=inputs)
+    assert result is not None
+
+
+def test_multiple_actions_example():
+    """Test crew that can handle multiple different actions."""
+    
+    researcher = Agent(role="Researcher", goal="Research topics", backstory="Expert researcher")
+    analyst = Agent(role="Analyst", goal="Analyze data", backstory="Expert analyst")
+    writer = Agent(role="Writer", goal="Write reports", backstory="Expert writer")
+    
+    research_task = Task(description="Research the topic", expected_output="Research findings", agent=researcher, tags=["research", "data_gathering"])
+    analysis_task = Task(description="Analyze the data", expected_output="Analysis results", agent=analyst, tags=["analysis", "forecast"])
+    writing_task = Task(description="Write the report", expected_output="Final report", agent=writer, tags=["writing", "summary"])
+    
+    crew = Crew(
+        agents=[researcher, analyst, writer],
+        tasks=[research_task, analysis_task, writing_task],
+        task_selector=Crew.create_tag_selector()
+    )
+    
+    research_result = crew.kickoff(inputs={"action": "research"})
+    assert research_result is not None
+    
+    analysis_result = crew.kickoff(inputs={"action": "analysis"})
+    assert analysis_result is not None
+    
+    writing_result = crew.kickoff(inputs={"action": "writing"})
+    assert writing_result is not None