mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-08 07:38:29 +00:00
dfc4255f2f
* docs: Fix major memory system documentation issues - Remove misleading deprecation warnings, fix confusing comments, clearly separate three memory approaches, provide accurate examples that match implementation * fix: Correct broken image paths in README - Update crewai_logo.png and asset.png paths to point to docs/images/ directory instead of docs/ directly * docs: Add system prompt transparency and customization guide - Add 'Understanding Default System Instructions' section to address black-box concerns - Document what CrewAI automatically injects into prompts - Provide code examples to inspect complete system prompts - Show 3 methods to override default instructions - Include observability integration examples with Langfuse - Add best practices for production prompt management * docs: Fix implementation accuracy issues in memory documentation - Fix Ollama embedding URL parameter and remove unsupported Cohere input_type parameter * docs: Reference observability docs instead of showing specific tool examples * docs: Reorganize knowledge documentation for better developer experience - Move quickstart examples right after overview for immediate hands-on experience - Create logical learning progression: basics → configuration → advanced → troubleshooting - Add comprehensive agent vs crew knowledge guide with working examples - Consolidate debugging and troubleshooting in dedicated section - Organize best practices by topic in accordion format - Improve content flow from simple concepts to advanced features - Ensure all examples are grounded in actual codebase implementation * docs: enhance custom LLM documentation with comprehensive examples and accurate imports * docs: reorganize observability tools into dedicated section with comprehensive overview and improved navigation * docs: rename how-to section to learn and add comprehensive overview page * docs: finalize documentation reorganization and update navigation labels * docs: enhance README with comprehensive badges, navigation links, and getting started video
123 lines
4.7 KiB
Plaintext
123 lines
4.7 KiB
Plaintext
---
|
|
title: Kickoff Crew Asynchronously
|
|
description: Kickoff a Crew Asynchronously
|
|
icon: rocket-launch
|
|
---
|
|
|
|
## Introduction
|
|
|
|
CrewAI provides the ability to kickoff a crew asynchronously, allowing you to start the crew execution in a non-blocking manner.
|
|
This feature is particularly useful when you want to run multiple crews concurrently or when you need to perform other tasks while the crew is executing.
|
|
|
|
## Asynchronous Crew Execution
|
|
|
|
To kickoff a crew asynchronously, use the `kickoff_async()` method. This method initiates the crew execution in a separate thread, allowing the main thread to continue executing other tasks.
|
|
|
|
### Method Signature
|
|
|
|
```python Code
|
|
def kickoff_async(self, inputs: dict) -> CrewOutput:
|
|
```
|
|
|
|
### Parameters
|
|
|
|
- `inputs` (dict): A dictionary containing the input data required for the tasks.
|
|
|
|
### Returns
|
|
|
|
- `CrewOutput`: An object representing the result of the crew execution.
|
|
|
|
## Potential Use Cases
|
|
|
|
- **Parallel Content Generation**: Kickoff multiple independent crews asynchronously, each responsible for generating content on different topics. For example, one crew might research and draft an article on AI trends, while another crew generates social media posts about a new product launch. Each crew operates independently, allowing content production to scale efficiently.
|
|
|
|
- **Concurrent Market Research Tasks**: Launch multiple crews asynchronously to conduct market research in parallel. One crew might analyze industry trends, while another examines competitor strategies, and yet another evaluates consumer sentiment. Each crew independently completes its task, enabling faster and more comprehensive insights.
|
|
|
|
- **Independent Travel Planning Modules**: Execute separate crews to independently plan different aspects of a trip. One crew might handle flight options, another handles accommodation, and a third plans activities. Each crew works asynchronously, allowing various components of the trip to be planned simultaneously and independently for faster results.
|
|
|
|
## Example: Single Asynchronous Crew Execution
|
|
|
|
Here's an example of how to kickoff a crew asynchronously using asyncio and awaiting the result:
|
|
|
|
```python Code
|
|
import asyncio
|
|
from crewai import Crew, Agent, Task
|
|
|
|
# Create an agent with code execution enabled
|
|
coding_agent = Agent(
|
|
role="Python Data Analyst",
|
|
goal="Analyze data and provide insights using Python",
|
|
backstory="You are an experienced data analyst with strong Python skills.",
|
|
allow_code_execution=True
|
|
)
|
|
|
|
# Create a task that requires code execution
|
|
data_analysis_task = Task(
|
|
description="Analyze the given dataset and calculate the average age of participants. Ages: {ages}",
|
|
agent=coding_agent,
|
|
expected_output="The average age of the participants."
|
|
)
|
|
|
|
# Create a crew and add the task
|
|
analysis_crew = Crew(
|
|
agents=[coding_agent],
|
|
tasks=[data_analysis_task]
|
|
)
|
|
|
|
# Async function to kickoff the crew asynchronously
|
|
async def async_crew_execution():
|
|
result = await analysis_crew.kickoff_async(inputs={"ages": [25, 30, 35, 40, 45]})
|
|
print("Crew Result:", result)
|
|
|
|
# Run the async function
|
|
asyncio.run(async_crew_execution())
|
|
```
|
|
|
|
## Example: Multiple Asynchronous Crew Executions
|
|
|
|
In this example, we'll show how to kickoff multiple crews asynchronously and wait for all of them to complete using `asyncio.gather()`:
|
|
|
|
```python Code
|
|
import asyncio
|
|
from crewai import Crew, Agent, Task
|
|
|
|
# Create an agent with code execution enabled
|
|
coding_agent = Agent(
|
|
role="Python Data Analyst",
|
|
goal="Analyze data and provide insights using Python",
|
|
backstory="You are an experienced data analyst with strong Python skills.",
|
|
allow_code_execution=True
|
|
)
|
|
|
|
# Create tasks that require code execution
|
|
task_1 = Task(
|
|
description="Analyze the first dataset and calculate the average age of participants. Ages: {ages}",
|
|
agent=coding_agent,
|
|
expected_output="The average age of the participants."
|
|
)
|
|
|
|
task_2 = Task(
|
|
description="Analyze the second dataset and calculate the average age of participants. Ages: {ages}",
|
|
agent=coding_agent,
|
|
expected_output="The average age of the participants."
|
|
)
|
|
|
|
# Create two crews and add tasks
|
|
crew_1 = Crew(agents=[coding_agent], tasks=[task_1])
|
|
crew_2 = Crew(agents=[coding_agent], tasks=[task_2])
|
|
|
|
# Async function to kickoff multiple crews asynchronously and wait for all to finish
|
|
async def async_multiple_crews():
|
|
result_1 = crew_1.kickoff_async(inputs={"ages": [25, 30, 35, 40, 45]})
|
|
result_2 = crew_2.kickoff_async(inputs={"ages": [20, 22, 24, 28, 30]})
|
|
|
|
# Wait for both crews to finish
|
|
results = await asyncio.gather(result_1, result_2)
|
|
|
|
for i, result in enumerate(results, 1):
|
|
print(f"Crew {i} Result:", result)
|
|
|
|
# Run the async function
|
|
asyncio.run(async_multiple_crews())
|
|
```
|