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* Clean up pipeline * Make versioning dynamic in templates * fix .env issues when openai is trying to use invalid keys * Fix type checker issue in pipeline * Fix tests.
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docs/getting-started/Create-a-New-CrewAI-Pipeline-Template-Method.md
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# Creating a CrewAI Pipeline Project | ||
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Welcome to the comprehensive guide for creating a new CrewAI pipeline project. This document will walk you through the steps to create, customize, and run your CrewAI pipeline project, ensuring you have everything you need to get started. | ||
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To learn more about CrewAI pipelines, visit the [CrewAI documentation](https://docs.crewai.com/core-concepts/Pipeline/). | ||
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## Prerequisites | ||
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Before getting started with CrewAI pipelines, make sure that you have installed CrewAI via pip: | ||
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```shell | ||
$ pip install crewai crewai-tools | ||
``` | ||
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The same prerequisites for virtual environments and Code IDEs apply as in regular CrewAI projects. | ||
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## Creating a New Pipeline Project | ||
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To create a new CrewAI pipeline project, you have two options: | ||
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1. For a basic pipeline template: | ||
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```shell | ||
$ crewai create pipeline <project_name> | ||
``` | ||
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2. For a pipeline example that includes a router: | ||
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```shell | ||
$ crewai create pipeline --router <project_name> | ||
``` | ||
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These commands will create a new project folder with the following structure: | ||
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``` | ||
<project_name>/ | ||
├── README.md | ||
├── poetry.lock | ||
├── pyproject.toml | ||
├── src/ | ||
│ └── <project_name>/ | ||
│ ├── __init__.py | ||
│ ├── main.py | ||
│ ├── crews/ | ||
│ │ ├── crew1/ | ||
│ │ │ ├── crew1.py | ||
│ │ │ └── config/ | ||
│ │ │ ├── agents.yaml | ||
│ │ │ └── tasks.yaml | ||
│ │ ├── crew2/ | ||
│ │ │ ├── crew2.py | ||
│ │ │ └── config/ | ||
│ │ │ ├── agents.yaml | ||
│ │ │ └── tasks.yaml | ||
│ ├── pipelines/ | ||
│ │ ├── __init__.py | ||
│ │ ├── pipeline1.py | ||
│ │ └── pipeline2.py | ||
│ └── tools/ | ||
│ ├── __init__.py | ||
│ └── custom_tool.py | ||
└── tests/ | ||
``` | ||
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## Customizing Your Pipeline Project | ||
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To customize your pipeline project, you can: | ||
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1. Modify the crew files in `src/<project_name>/crews/` to define your agents and tasks for each crew. | ||
2. Modify the pipeline files in `src/<project_name>/pipelines/` to define your pipeline structure. | ||
3. Modify `src/<project_name>/main.py` to set up and run your pipelines. | ||
4. Add your environment variables into the `.env` file. | ||
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### Example: Defining a Pipeline | ||
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Here's an example of how to define a pipeline in `src/<project_name>/pipelines/normal_pipeline.py`: | ||
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```python | ||
from crewai import Pipeline | ||
from crewai.project import PipelineBase | ||
from ..crews.normal_crew import NormalCrew | ||
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@PipelineBase | ||
class NormalPipeline: | ||
def __init__(self): | ||
# Initialize crews | ||
self.normal_crew = NormalCrew().crew() | ||
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def create_pipeline(self): | ||
return Pipeline( | ||
stages=[ | ||
self.normal_crew | ||
] | ||
) | ||
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async def kickoff(self, inputs): | ||
pipeline = self.create_pipeline() | ||
results = await pipeline.kickoff(inputs) | ||
return results | ||
``` | ||
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### Annotations | ||
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The main annotation you'll use for pipelines is `@PipelineBase`. This annotation is used to decorate your pipeline classes, similar to how `@CrewBase` is used for crews. | ||
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## Installing Dependencies | ||
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To install the dependencies for your project, use Poetry: | ||
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```shell | ||
$ cd <project_name> | ||
$ poetry lock | ||
$ poetry install | ||
``` | ||
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## Running Your Pipeline Project | ||
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To run your pipeline project, use the following command: | ||
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```shell | ||
$ crewai run | ||
``` | ||
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or | ||
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```shell | ||
$ poetry run <project_name> | ||
``` | ||
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This will initialize your pipeline and begin task execution as defined in your `main.py` file. | ||
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## Deploying Your Pipeline Project | ||
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Pipelines can be deployed in the same way as regular CrewAI projects. The easiest way is through [CrewAI+](https://www.crewai.com/crewaiplus), where you can deploy your pipeline in a few clicks. | ||
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Remember, when working with pipelines, you're orchestrating multiple crews to work together in a sequence or parallel fashion. This allows for more complex workflows and information processing tasks. |
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