mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-07 07:08:31 +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
53 lines
1.6 KiB
Plaintext
53 lines
1.6 KiB
Plaintext
---
|
|
title: Kickoff Crew for Each
|
|
description: Kickoff Crew for Each Item in a List
|
|
icon: at
|
|
---
|
|
|
|
## Introduction
|
|
|
|
CrewAI provides the ability to kickoff a crew for each item in a list, allowing you to execute the crew for each item in the list.
|
|
This feature is particularly useful when you need to perform the same set of tasks for multiple items.
|
|
|
|
## Kicking Off a Crew for Each Item
|
|
|
|
To kickoff a crew for each item in a list, use the `kickoff_for_each()` method.
|
|
This method executes the crew for each item in the list, allowing you to process multiple items efficiently.
|
|
|
|
Here's an example of how to kickoff a crew for each item in a list:
|
|
|
|
```python Code
|
|
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 calculated from the dataset"
|
|
)
|
|
|
|
# Create a crew and add the task
|
|
analysis_crew = Crew(
|
|
agents=[coding_agent],
|
|
tasks=[data_analysis_task],
|
|
verbose=True,
|
|
memory=False
|
|
)
|
|
|
|
datasets = [
|
|
{ "ages": [25, 30, 35, 40, 45] },
|
|
{ "ages": [20, 25, 30, 35, 40] },
|
|
{ "ages": [30, 35, 40, 45, 50] }
|
|
]
|
|
|
|
# Execute the crew
|
|
result = analysis_crew.kickoff_for_each(inputs=datasets)
|
|
``` |