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updating docs

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João Moura
2024-02-26 13:38:14 -03:00
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docs/core-concepts/Agents.md
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@@ -15,26 +15,27 @@ description: What are crewAI Agents and how to use them.
## Agent Attributes
| Attribute | Description |
| :---------- | :----------------------------------- |
| **Role** | Defines the agent's function within the crew. It determines the kind of tasks the agent is best suited for. |
| **Goal** | The individual objective that the agent aims to achieve. It guides the agent's decision-making process. |
| **Backstory** | Provides context to the agent's role and goal, enriching the interaction and collaboration dynamics. |
| **LLM** | The language model used by the agent to process and generate text. |
| **Tools** | Set of capabilities or functions that the agent can use to perform tasks. Tools can be shared or exclusive to specific agents. |
| **Function Calling LLM** | The language model used by this agent to call functions, if none is passed the same main llm for each agent will be used. |
| **Max Iter** | The maximum number of iterations the agent can perform before forced to give its best answer |
| **Max RPM** | The maximum number of requests per minute the agent can perform to avoid rate limits |
| **Verbose** | This allow you to actually see what is going on during the Crew execution. |
| **Allow Delegation** | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. |
| **Step Callback** | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback` |
| Attribute | Description |
| :------------------ | :----------------------------------- |
| **Role** | Defines the agent's function within the crew. It determines the kind of tasks the agent is best suited for. |
| **Goal** | The individual objective that the agent aims to achieve. It guides the agent's decision-making process. |
| **Backstory** | Provides context to the agent's role and goal, enriching the interaction and collaboration dynamics. |
| **LLM** | The language model used by the agent to process and generate text. Defaults to using OpenAI's GPT-4 (`ChatOpenAI`), unless another model is specified through the environment variable "OPENAI_MODEL_NAME". |
| **Tools** | Set of capabilities or functions that the agent can use to perform tasks. Tools can be shared or exclusive to specific agents. It's an attribute that can be set during the initialization of an agent. |
| **Function Calling LLM** | The language model used by this agent to call functions. It is an optional field and, if not provided, the behavior of defaulting to the main `llm` is implicit. |
| **Max Iter** | The maximum number of iterations the agent can perform before being forced to give its best answer. Default is `15`. |
| **Max RPM** | The maximum number of requests per minute the agent can perform to avoid rate limits. It's optional and can be left unspecified. |
| **Verbose** | Enables detailed logging of the agent's execution for debugging or monitoring purposes when set to True. Default is `False` |
| **Allow Delegation**| Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. |
| **Step Callback** | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback`. |
| **Memory** | Indicates whether the agent should have memory or not, with a default value of False. This impacts the agent's ability to remember past interactions. Default is `False` |
## Creating an Agent
!!! note "Agent Interaction"
Agents can interact with each other using the CrewAI's built-in delegation and communication mechanisms.<br/>This allows for dynamic task management and problem-solving within the crew.
To create an agent, you would typically initialize an instance of the `Agent` class with the desired properties. Here's a conceptual example:
To create an agent, you would typically initialize an instance of the `Agent` class with the desired properties. Here's a conceptual example including all attributes:
```python
# Example: Creating an agent with all attributes
@@ -48,14 +49,15 @@ agent = Agent(
to the business.
You're currently working on a project to analyze the
performance of our marketing campaigns.""",
tools=[my_tool1, my_tool2],
llm=my_llm,
function_calling_llm=my_llm,
max_iter=10,
max_rpm=10,
verbose=True,
allow_delegation=True,
step_callback=my_intermediate_step_callback
tools=[my_tool1, my_tool2], # Optional
llm=my_llm, # Optional
function_calling_llm=my_llm, # Optional
max_iter=15, # Optional
max_rpm=None, # Optional
verbose=True, # Optional
allow_delegation=True, # Optional
step_callback=my_intermediate_step_callback, # Optional
memory=True # Optional
)
```