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adding new docs

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João Moura
2025-04-07 02:46:22 -04:00
parent d216edb022
commit 918c0589eb
7 changed files with 103 additions and 15 deletions
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14
docs/concepts/agents.mdx
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@@ -18,6 +18,18 @@ In the CrewAI framework, an `Agent` is an autonomous unit that can:
Think of an agent as a specialized team member with specific skills, expertise, and responsibilities. For example, a `Researcher` agent might excel at gathering and analyzing information, while a `Writer` agent might be better at creating content.
</Tip>
<Note type="info" title="Enterprise Enhancement: Visual Agent Builder">
CrewAI Enterprise includes a Visual Agent Builder that simplifies agent creation and configuration without writing code. Design your agents visually and test them in real-time.
![Visual Agent Builder Screenshot](../images/enterprise/crew-studio-quickstart)
The Visual Agent Builder enables:
- Intuitive agent configuration with form-based interfaces
- Real-time testing and validation
- Template library with pre-configured agent types
- Easy customization of agent attributes and behaviors
</Note>
## Agent Attributes
| Attribute | Parameter | Type | Description |
@@ -233,7 +245,7 @@ custom_agent = Agent(
#### Code Execution
- `allow_code_execution`: Must be True to run code
- `code_execution_mode`:
- `code_execution_mode`:
- `"safe"`: Uses Docker (recommended for production)
- `"unsafe"`: Direct execution (use only in trusted environments)

28
docs/concepts/event-listener.mdx
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@@ -18,6 +18,20 @@ CrewAI uses an event bus architecture to emit events throughout the execution li
When specific actions occur in CrewAI (like a Crew starting execution, an Agent completing a task, or a tool being used), the system emits corresponding events. You can register handlers for these events to execute custom code when they occur.
<Note type="info" title="Enterprise Enhancement: Prompt Tracing">
CrewAI Enterprise provides a built-in Prompt Tracing feature that leverages the event system to track, store, and visualize all prompts, completions, and associated metadata. This provides powerful debugging capabilities and transparency into your agent operations.
![Prompt Tracing Dashboard](../images/enterprise/prompt-tracing.png)
With Prompt Tracing you can:
- View the complete history of all prompts sent to your LLM
- Track token usage and costs
- Debug agent reasoning failures
- Share prompt sequences with your team
- Compare different prompt strategies
- Export traces for compliance and auditing
</Note>
## Creating a Custom Event Listener
To create a custom event listener, you need to:
@@ -40,17 +54,17 @@ from crewai.utilities.events.base_event_listener import BaseEventListener
class MyCustomListener(BaseEventListener):
def __init__(self):
super().__init__()
def setup_listeners(self, crewai_event_bus):
@crewai_event_bus.on(CrewKickoffStartedEvent)
def on_crew_started(source, event):
print(f"Crew '{event.crew_name}' has started execution!")
@crewai_event_bus.on(CrewKickoffCompletedEvent)
def on_crew_completed(source, event):
print(f"Crew '{event.crew_name}' has completed execution!")
print(f"Output: {event.output}")
@crewai_event_bus.on(AgentExecutionCompletedEvent)
def on_agent_execution_completed(source, event):
print(f"Agent '{event.agent.role}' completed task")
@@ -83,7 +97,7 @@ my_listener = MyCustomListener()
class MyCustomCrew:
# Your crew implementation...
def crew(self):
return Crew(
agents=[...],
@@ -106,7 +120,7 @@ my_listener = MyCustomListener()
class MyCustomFlow(Flow):
# Your flow implementation...
@start()
def first_step(self):
# ...
@@ -324,9 +338,9 @@ with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(CrewKickoffStartedEvent)
def temp_handler(source, event):
print("This handler only exists within this context")
# Do something that emits events
# Outside the context, the temporary handler is removed
```

16
docs/concepts/tasks.mdx
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@@ -12,6 +12,18 @@ Tasks provide all necessary details for execution, such as a description, the ag
Tasks within CrewAI can be collaborative, requiring multiple agents to work together. This is managed through the task properties and orchestrated by the Crew's process, enhancing teamwork and efficiency.
<Note type="info" title="Enterprise Enhancement: Visual Task Builder">
CrewAI Enterprise includes a Visual Task Builder in Crew Studio that simplifies complex task creation and chaining. Design your task flows visually and test them in real-time without writing code.
![Task Builder Screenshot](../images/enterprise/crew-studio-quickstart.png)
The Visual Task Builder enables:
- Drag-and-drop task creation
- Visual task dependencies and flow
- Real-time testing and validation
- Easy sharing and collaboration
</Note>
### Task Execution Flow
Tasks can be executed in two ways:
@@ -414,7 +426,7 @@ It's also important to note that the output of the final task of a crew becomes
### Using `output_pydantic`
The `output_pydantic` property allows you to define a Pydantic model that the task output should conform to. This ensures that the output is not only structured but also validated according to the Pydantic model.
Here’s an example demonstrating how to use output_pydantic:
Here's an example demonstrating how to use output_pydantic:
```python Code
import json
@@ -495,7 +507,7 @@ In this example:
### Using `output_json`
The `output_json` property allows you to define the expected output in JSON format. This ensures that the task's output is a valid JSON structure that can be easily parsed and used in your application.
Here’s an example demonstrating how to use `output_json`:
Here's an example demonstrating how to use `output_json`:
```python Code
import json

16
docs/concepts/tools.mdx
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@@ -15,6 +15,18 @@ A tool in CrewAI is a skill or function that agents can utilize to perform vario
This includes tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools),
enabling everything from simple searches to complex interactions and effective teamwork among agents.
<Note type="info" title="Enterprise Enhancement: Tools Repository">
CrewAI Enterprise provides a comprehensive Tools Repository with pre-built integrations for common business systems and APIs. Deploy agents with enterprise tools in minutes instead of days.
![Tools Repository Screenshot](../images/enterprise/tools-repository.png)
The Enterprise Tools Repository includes:
- Pre-built connectors for popular enterprise systems
- Custom tool creation interface
- Version control and sharing capabilities
- Security and compliance features
</Note>
## Key Characteristics of Tools
- **Utility**: Crafted for tasks such as web searching, data analysis, content generation, and agent collaboration.
@@ -79,7 +91,7 @@ research = Task(
)
write = Task(
description='Write an engaging blog post about the AI industry, based on the research analyst’s summary. Draw inspiration from the latest blog posts in the directory.',
description='Write an engaging blog post about the AI industry, based on the research analyst's summary. Draw inspiration from the latest blog posts in the directory.',
expected_output='A 4-paragraph blog post formatted in markdown with engaging, informative, and accessible content, avoiding complex jargon.',
agent=writer,
output_file='blog-posts/new_post.md' # The final blog post will be saved here
@@ -141,7 +153,7 @@ Here is a list of the available tools and their descriptions:
## Creating your own Tools
<Tip>
Developers can craft `custom tools` tailored for their agent’s needs or
Developers can craft `custom tools` tailored for their agent's needs or
utilize pre-built options.
</Tip>