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João Moura
2024-03-03 20:51:34 -03:00
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docs/core-concepts/Crews.md
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@@ -1,3 +1,4 @@
```markdown
---
title: crewAI Crews
description: Understanding and utilizing crews in the crewAI framework.
@@ -9,20 +10,20 @@ description: Understanding and utilizing crews in the crewAI framework.
## Crew Attributes
| Attribute | Description |
| :------------------- | :----------------------------------------------------------- |
| **Tasks** | A list of tasks assigned to the crew. |
| **Agents** | A list of agents that are part of the crew. |
| **Process** | The process flow (e.g., sequential, hierarchical) the crew follows. |
| **Verbose** | The verbosity level for logging during execution. |
| **Manager LLM** | The language model used by the manager agent in a hierarchical process. **Required when using a hierarchical process.** |
| **Function Calling LLM** | If passed crew will use this LLM to do function calling for tools for all agents in the crew |
| **Config** | Optional configuration settings for the crew, in `Json` or `Dict[str, Any]` format. |
| **Max RPM** | Maximum requests per minute the crew adheres to during execution. |
| **Language** | Language used for the crew, defaults to English. |
| **Full Output** | Whether the crew should return the full output with all tasks outputs or just the final output. |
| **Step Callback** | A function that is called after each step of every agent. This can be used to log the agent's actions or to perform other operations; it won't override the agent-specific `step_callback`. |
| **Share Crew** | Whether you want to share the complete crew information and execution with the crewAI team to make the library better, and allow us to train models. |
| Attribute | Description |
| :---------------------- | :----------------------------------------------------------- |
| **Tasks** | A list of tasks assigned to the crew. |
| **Agents** | A list of agents that are part of the crew. |
| **Process** *(optional)* | The process flow (e.g., sequential, hierarchical) the crew follows. |
| **Verbose** *(optional)* | The verbosity level for logging during execution. |
| **Manager LLM** *(optional)* | The language model used by the manager agent in a hierarchical process. **Required when using a hierarchical process.** |
| **Function Calling LLM** *(optional)* | If passed, the crew will use this LLM to do function calling for tools for all agents in the crew. Each agent can have its own LLM, which overrides the crew's LLM for function calling. |
| **Config** *(optional)* | Optional configuration settings for the crew, in `Json` or `Dict[str, Any]` format. |
| **Max RPM** *(optional)* | Maximum requests per minute the crew adheres to during execution. |
| **Language** *(optional)* | Language used for the crew, defaults to English. |
| **Full Output** *(optional)* | Whether the crew should return the full output with all tasks outputs or just the final output. |
| **Step Callback** *(optional)* | A function that is called after each step of every agent. This can be used to log the agent's actions or to perform other operations; it won't override the agent-specific `step_callback`. |
| **Share Crew** *(optional)* | Whether you want to share the complete crew information and execution with the crewAI team to make the library better, and allow us to train models. |
!!! note "Crew Max RPM"
The `max_rpm` attribute sets the maximum number of requests per minute the crew can perform to avoid rate limits and will override individual agents' `max_rpm` settings if you set it.
@@ -47,12 +48,19 @@ researcher = Agent(
writer = Agent(
role='Content Writer',
goal='Write engaging articles on AI discoveries'
goal='Write engaging articles on AI discoveries',
verbose=True
)
# Create tasks for the agents
research_task = Task(description='Identify breakthrough AI technologies', agent=researcher)
write_article_task = Task(description='Draft an article on the latest AI technologies', agent=writer)
research_task = Task(
description='Identify breakthrough AI technologies',
agent=researcher
)
write_article_task = Task(
description='Draft an article on the latest AI technologies',
agent=writer
)
# Assemble the crew with a sequential process
my_crew = Crew(
@@ -60,14 +68,25 @@ my_crew = Crew(
tasks=[research_task, write_article_task],
process=Process.sequential,
full_output=True,
verbose=True
verbose=True,
)
```
## Crew Usage Metrics
After the crew execution, you can access the `usage_metrics` attribute to view the language model (LLM) usage metrics for all tasks executed by the crew. This provides insights into operational efficiency and areas for improvement.
```python
# Access the crew's usage metrics
crew = Crew(agents=[agent1, agent2], tasks=[task1, task2])
crew.kickoff()
print(crew.usage_metrics)
```
## Crew Execution Process
- **Sequential Process**: Tasks are executed one after another, allowing for a linear flow of work.
- **Hierarchical Process**: A manager agent coordinates the crew, delegating tasks and validating outcomes before proceeding. **Note**: A `manager_llm` is required for this process.
- **Hierarchical Process**: A manager agent coordinates the crew, delegating tasks and validating outcomes before proceeding. **Note**: A `manager_llm` is required for this process and it's essential for validating the process flow.
### Kicking Off a Crew
@@ -77,4 +96,3 @@ Once your crew is assembled, initiate the workflow with the `kickoff()` method.
# Start the crew's task execution
result = my_crew.kickoff()
print(result)
```