Removing LangChain and Rebuilding Executor (#1322)

* rebuilding executor

* removing langchain

* Making all tests good

* fixing types and adding ability for nor using system prompts

* improving types

* pleasing the types gods

* pleasing the types gods

* fixing parser, tools and executor

* making sure all tests pass

* final pass

* fixing type

* Updating Docs

* preparing to cut new version
This commit is contained in:
João Moura
2024-09-16 14:14:04 -03:00
committed by GitHub
parent 322780a5f3
commit e77442cf34
177 changed files with 27272 additions and 1618561 deletions

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@@ -71,25 +71,59 @@ To customize your pipeline project, you can:
3. Modify `src/<project_name>/main.py` to set up and run your pipelines.
4. Add your environment variables into the `.env` file.
### Example: Defining a Pipeline
## Example 1: Defining a Two-Stage Sequential Pipeline
Here's an example of how to define a pipeline in `src/<project_name>/pipelines/normal_pipeline.py`:
Here's an example of how to define a pipeline with sequential stages in `src/<project_name>/pipelines/pipeline.py`:
```python
from crewai import Pipeline
from crewai.project import PipelineBase
from ..crews.normal_crew import NormalCrew
from ..crews.research_crew.research_crew import ResearchCrew
from ..crews.write_x_crew.write_x_crew import WriteXCrew
@PipelineBase
class NormalPipeline:
class SequentialPipeline:
def __init__(self):
# Initialize crews
self.normal_crew = NormalCrew().crew()
self.research_crew = ResearchCrew().crew()
self.write_x_crew = WriteXCrew().crew()
def create_pipeline(self):
return Pipeline(
stages=[
self.normal_crew
self.research_crew,
self.write_x_crew
]
)
async def kickoff(self, inputs):
pipeline = self.create_pipeline()
results = await pipeline.kickoff(inputs)
return results
```
## Example 2: Defining a Two-Stage Pipeline with Parallel Execution
```python
from crewai import Pipeline
from crewai.project import PipelineBase
from ..crews.research_crew.research_crew import ResearchCrew
from ..crews.write_x_crew.write_x_crew import WriteXCrew
from ..crews.write_linkedin_crew.write_linkedin_crew import WriteLinkedInCrew
@PipelineBase
class ParallelExecutionPipeline:
def __init__(self):
# Initialize crews
self.research_crew = ResearchCrew().crew()
self.write_x_crew = WriteXCrew().crew()
self.write_linkedin_crew = WriteLinkedInCrew().crew()
def create_pipeline(self):
return Pipeline(
stages=[
self.research_crew,
[self.write_x_crew, self.write_linkedin_crew] # Parallel execution
]
)
@@ -126,4 +160,4 @@ This will initialize your pipeline and begin task execution as defined in your `
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.
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.
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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@@ -1,5 +1,7 @@
---
title: Starting a New CrewAI Project - Using Template
description: A comprehensive guide to starting a new CrewAI project, including the latest updates and project setup methods.
---
@@ -21,6 +23,7 @@ $ pip install 'crewai[tools]'
```
## Creating a New Project
In this example, we will be using poetry as our virtual environment manager.
To create a new CrewAI project, run the following CLI command:
@@ -95,10 +98,13 @@ research_candidates_task:
```
### Referencing Variables:
Your defined functions with the same name will be used. For example, you can reference the agent for specific tasks from task.yaml file. Ensure your annotated agent and function name is the same otherwise your task won't recognize the reference properly.
Your defined functions with the same name will be used. For example, you can reference the agent for specific tasks from `tasks.yaml` file. Ensure your annotated agent and function name are the same; otherwise, your task won't recognize the reference properly.
#### Example References
agent.yaml
`agents.yaml`
```yaml
email_summarizer:
role: >
@@ -110,7 +116,8 @@ email_summarizer:
llm: mixtal_llm
```
task.yaml
`tasks.yaml`
```yaml
email_summarizer_task:
description: >
@@ -123,37 +130,34 @@ email_summarizer_task:
- research_task
```
Use the annotations to properly reference the agent and task in the crew.py file.
Use the annotations to properly reference the agent and task in the `crew.py` file.
### Annotations include:
* [@agent](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L17)
* [@task](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L4)
* [@crew](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L69)
* [@llm](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L23)
* [@tool](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L39)
* [@callback](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L44)
* [@output_json](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L29)
* [@output_pydantic](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L34)
* [@cache_handler](https://github.com/crewAIInc/crewAI/blob/97d7bfb52ad49a9f04db360e1b6612d98c91971e/src/crewai/project/annotations.py#L49)
crew.py
```py
* `@agent`
* `@task`
* `@crew`
* `@tool`
* `@callback`
* `@output_json`
* `@output_pydantic`
* `@cache_handler`
`crew.py`
```python
# ...
@llm
def mixtal_llm(self):
return ChatGroq(temperature=0, model_name="mixtral-8x7b-32768")
@agent
def email_summarizer(self) -> Agent:
return Agent(
config=self.agents_config["email_summarizer"],
)
@agent
def email_summarizer(self) -> Agent:
return Agent(
config=self.agents_config["email_summarizer"],
)
## ...other tasks defined
@task
def email_summarizer_task(self) -> Task:
return Task(
config=self.tasks_config["email_summarizer_task"],
)
@task
def email_summarizer_task(self) -> Task:
return Task(
config=self.tasks_config["email_summarizer_task"],
)
# ...
```
@@ -204,6 +208,7 @@ To run your project, use the following command:
```shell
$ crewai run
```
This will initialize your crew of AI agents and begin task execution as defined in your configuration in the `main.py` file.
### Replay Tasks from Latest Crew Kickoff