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https://github.com/crewAIInc/crewAI.git
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docs: enhance decorator documentation and update LLM syntax
This commit is contained in:
Tony Kipkemboi
@@ -75,56 +75,6 @@ Follow the steps below to get crewing! 🚣♂️
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```
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</Step>
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<Step title="Modify your `crew.py` file">
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```python crew.py
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# src/latest_ai_development/crew.py
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from crewai import Agent, Crew, Process, Task
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from crewai.project import CrewBase, agent, crew, task
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from crewai_tools import SerperDevTool
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@CrewBase
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class LatestAiDevelopmentCrew():
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"""LatestAiDevelopment crew"""
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@agent
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def researcher(self) -> Agent:
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return Agent(
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config=self.agents_config['researcher'],
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verbose=True,
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tools=[SerperDevTool()]
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)
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@agent
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def reporting_analyst(self) -> Agent:
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return Agent(
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config=self.agents_config['reporting_analyst'],
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verbose=True
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)
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@task
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def research_task(self) -> Task:
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return Task(
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config=self.tasks_config['research_task'],
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)
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@task
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def reporting_task(self) -> Task:
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return Task(
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config=self.tasks_config['reporting_task'],
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output_file='output/report.md' # This is the file that will be contain the final report.
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)
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@crew
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def crew(self) -> Crew:
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"""Creates the LatestAiDevelopment crew"""
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return Crew(
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agents=self.agents, # Automatically created by the @agent decorator
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tasks=self.tasks, # Automatically created by the @task decorator
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process=Process.sequential,
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verbose=True,
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)
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```
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</Step>
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<Step title="[Optional] Add before and after crew functions">
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```python crew.py
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# src/latest_ai_development/crew.py
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from crewai import Agent, Crew, Process, Task
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@@ -145,6 +95,16 @@ Follow the steps below to get crewing! 🚣♂️
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print(f"After kickoff function with result: {result}")
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return result # You can return the result or modify it as needed
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@callback
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def log_progress(self, task: Task, output: str):
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"""Log task completion progress."""
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print(f"\n{'='*50}")
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print(f"Task Completed: {task.description}")
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print(f"Agent: {task.agent.role}")
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print(f"Output Length: {len(output)} characters")
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print(f"Completed at: {datetime.now().isoformat()}")
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print(f"{'='*50}\n")
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# ... remaining code
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```
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</Step>
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@@ -301,38 +261,166 @@ Use the annotations to properly reference the agent and task in the `crew.py` fi
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### Annotations include:
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* `@agent`
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* `@task`
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* `@crew`
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* `@tool`
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* `@before_kickoff`
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* `@after_kickoff`
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* `@callback`
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* `@output_json`
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* `@output_pydantic`
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* `@cache_handler`
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Here are examples of how to use each annotation in your CrewAI project, and when you should use them:
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```python crew.py
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# ...
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#### @agent
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Used to define an agent in your crew. Use this when:
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- You need to create a specialized AI agent with a specific role
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- You want the agent to be automatically collected and managed by the crew
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- You need to reuse the same agent configuration across multiple tasks
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```python
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@agent
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def email_summarizer(self) -> Agent:
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def research_agent(self) -> Agent:
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return Agent(
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config=self.agents_config["email_summarizer"],
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role="Research Analyst",
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goal="Conduct thorough research on given topics",
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backstory="Expert researcher with years of experience in data analysis",
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tools=[SerperDevTool()],
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verbose=True
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)
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@task
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def email_summarizer_task(self) -> Task:
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return Task(
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config=self.tasks_config["email_summarizer_task"],
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)
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# ...
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```
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<Tip>
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In addition to the [sequential process](../how-to/sequential-process), you can use the [hierarchical process](../how-to/hierarchical-process),
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which automatically assigns a manager to the defined crew to properly coordinate the planning and execution of tasks through delegation and validation of results.
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You can learn more about the core concepts [here](/concepts).
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</Tip>
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#### @task
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Used to define a task that can be executed by agents. Use this when:
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- You need to define a specific piece of work for an agent
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- You want tasks to be automatically sequenced and managed
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- You need to establish dependencies between different tasks
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```python
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@task
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def research_task(self) -> Task:
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return Task(
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description="Research the latest developments in AI technology",
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expected_output="A comprehensive report on AI advancements",
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agent=self.research_agent(),
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output_file="output/research.md"
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)
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```
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#### @crew
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Used to define your crew configuration. Use this when:
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- You want to automatically collect all @agent and @task definitions
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- You need to specify how tasks should be processed (sequential or hierarchical)
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- You want to set up crew-wide configurations
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```python
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@crew
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def research_crew(self) -> Crew:
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return Crew(
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agents=self.agents, # Automatically collected from @agent methods
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tasks=self.tasks, # Automatically collected from @task methods
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process=Process.sequential,
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verbose=True
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)
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```
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#### @tool
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Used to create custom tools for your agents. Use this when:
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- You need to give agents specific capabilities (like web search, data analysis)
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- You want to encapsulate external API calls or complex operations
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- You need to share functionality across multiple agents
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```python
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@tool
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def web_search_tool(query: str, max_results: int = 5) -> list[str]:
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"""
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Search the web for information.
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Args:
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query: The search query
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max_results: Maximum number of results to return
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Returns:
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List of search results
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"""
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# Implement your search logic here
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return [f"Result {i} for: {query}" for i in range(max_results)]
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```
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#### @before_kickoff
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Used to execute logic before the crew starts. Use this when:
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- You need to validate or preprocess input data
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- You want to set up resources or configurations before execution
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- You need to perform any initialization logic
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```python
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@before_kickoff
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def validate_inputs(self, inputs: Optional[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
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"""Validate and preprocess inputs before the crew starts."""
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if inputs is None:
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return None
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if 'topic' not in inputs:
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raise ValueError("Topic is required")
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# Add additional context
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inputs['timestamp'] = datetime.now().isoformat()
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inputs['topic'] = inputs['topic'].strip().lower()
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return inputs
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```
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#### @after_kickoff
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Used to process results after the crew completes. Use this when:
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- You need to format or transform the final output
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- You want to perform cleanup operations
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- You need to save or log the results in a specific way
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```python
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@after_kickoff
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def process_results(self, result: CrewOutput) -> CrewOutput:
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"""Process and format the results after the crew completes."""
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result.raw = result.raw.strip()
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result.raw = f"""
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# Research Results
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Generated on: {datetime.now().isoformat()}
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{result.raw}
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"""
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return result
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```
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#### @callback
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Used to handle events during crew execution. Use this when:
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- You need to monitor task progress
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- You want to log intermediate results
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- You need to implement custom progress tracking or metrics
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```python
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@callback
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def log_task_completion(self, task: Task, output: str):
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"""Log task completion details for monitoring."""
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print(f"Task '{task.description}' completed")
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print(f"Output length: {len(output)} characters")
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print(f"Agent used: {task.agent.role}")
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print("-" * 50)
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```
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#### @cache_handler
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Used to implement custom caching for task results. Use this when:
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- You want to avoid redundant expensive operations
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- You need to implement custom cache storage or expiration logic
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- You want to persist results between runs
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```python
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@cache_handler
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def custom_cache(self, key: str) -> Optional[str]:
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"""Custom cache implementation for storing task results."""
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cache_file = f"cache/{key}.json"
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if os.path.exists(cache_file):
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with open(cache_file, 'r') as f:
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data = json.load(f)
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# Check if cache is still valid (e.g., not expired)
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if datetime.fromisoformat(data['timestamp']) > datetime.now() - timedelta(days=1):
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return data['result']
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return None
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```
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<Note>
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These decorators are part of the CrewAI framework and help organize your crew's structure by automatically collecting agents, tasks, and handling various lifecycle events.
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They should be used within a class decorated with `@CrewBase`.
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</Note>
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### Replay Tasks from Latest Crew Kickoff
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