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18 Commits

Author SHA1 Message Date
Eduardo Chiarotti
1cd1729a87 feat: Add crewai install to the docs and force now crewai run 2024-08-16 22:11:32 -03:00
Eduardo Chiarotti
3e9cffe740 feat: Add crewai install CLI command 2024-08-16 22:05:01 -03:00
Rip&Tear
ddda8f6bda Merge pull request #1194 from crewAIInc/docs_update
Updated Documentation to fix minor issues + minor .github fixes
2024-08-17 08:14:17 +08:00
Brandon Hancock (bhancock_ai)
bf7372fefa Adding Autocomplete to OSS (#1198)
* Cleaned up model_config

* Fix pydantic issues

* 99% done with autocomplete

* fixed test issues

* Fix type checking issues
2024-08-16 15:04:21 -04:00
Brandon Hancock (bhancock_ai)
3451b6fc7a Clean up pipeline (#1187)
* 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.
2024-08-16 14:47:28 -04:00
Vini Brasil
dbf2570353 Add name and expected_output to TaskOutput (#1199)
* Add name and expected_output to TaskOutput

This commit adds task information to the TaskOutput class. This is
useful to provide extra context to callbacks.

* Populate task name from function names

This commit populates task name from function names when using
annotations.
2024-08-15 22:24:41 +01:00
Eduardo Chiarotti
d0707fac91 feat: Add bandit ci pipeline (#1200)
* feat: Add bandit ci pipeline

* feat: add useforsecurty false for bandit pipeline

* feat: Add report only for High severity issues
2024-08-15 18:19:57 -03:00
theCyberTech
35ebdd6022 Updated Documentaion to fix navigation link for pipelin feature, removed legacy md fiel from .github & added missing config.yml config to remove custom issues from user access 2024-08-15 16:35:05 +08:00
Rip&Tear
92a77e5cac Merge pull request #1183 from crewAIInc/feature-templates
Feature templates
2024-08-15 11:29:36 +08:00
Rip&Tear
a2922c9ad5 Merge pull request #1182 from crewAIInc/git-temaplates
updated bug report template to yml for more control
2024-08-15 11:28:31 +08:00
Eduardo Chiarotti
9f9b52dd26 fix: Fix planning_llm issue (#1189)
* fix: Fix planning_llm issue

* fix: add poetry.lock updated version

* fix: type checking issues

* fix: tests
2024-08-14 18:54:53 -03:00
theCyberTech
2482c7ab68 Addded feature request template in YAML format
Added config .yml to remove blank template
2024-08-14 15:49:55 +08:00
theCyberTech
7fdabda97e updated bug report template to yml for more control 2024-08-14 15:08:59 +08:00
Eduardo Chiarotti
7306414de7 docs: fix references to annotations (#1176) 2024-08-13 12:58:12 -03:00
Eduardo Chiarotti
97d7bfb52a docs: Update Dalle, FileWrite, Nl2Sql and Side menu Tools (#1175)
* docs: Update Dalle, FileWrite, Nl2Sql and Side menu Tools

* docs: remove unused phrase

* docs: fix identation
2024-08-13 12:29:34 -03:00
Rafael Miller
9f85a2a011 Added Firecrawl tools to docs (#628) 2024-08-13 12:09:11 -03:00
João Moura
ab47d276db preparing new version 2024-08-11 22:07:54 -03:00
João Moura
44e38b1d5e Fixing telemetry condition that was missing 2024-08-11 22:07:45 -03:00
49 changed files with 928 additions and 457 deletions

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@@ -1,35 +0,0 @@
---
name: Bug report
about: Create a report to help us improve CrewAI
title: "[BUG]"
labels: bug
assignees: ''
---
**Description**
Provide a clear and concise description of what the bug is.
**Steps to Reproduce**
Provide a step-by-step process to reproduce the behavior:
**Expected behavior**
A clear and concise description of what you expected to happen.
**Screenshots/Code snippets**
If applicable, add screenshots or code snippets to help explain your problem.
**Environment Details:**
- **Operating System**: [e.g., Ubuntu 20.04, macOS Catalina, Windows 10]
- **Python Version**: [e.g., 3.8, 3.9, 3.10]
- **crewAI Version**: [e.g., 0.30.11]
- **crewAI Tools Version**: [e.g., 0.2.6]
**Logs**
Include relevant logs or error messages if applicable.
**Possible Solution**
Have a solution in mind? Please suggest it here, or write "None".
**Additional context**
Add any other context about the problem here.

116
.github/ISSUE_TEMPLATE/bug_report.yml vendored Normal file
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@@ -0,0 +1,116 @@
name: Bug report
description: Create a report to help us improve CrewAI
title: "[BUG]"
labels: ["bug"]
assignees: []
body:
- type: textarea
id: description
attributes:
label: Description
description: Provide a clear and concise description of what the bug is.
validations:
required: true
- type: textarea
id: steps-to-reproduce
attributes:
label: Steps to Reproduce
description: Provide a step-by-step process to reproduce the behavior.
placeholder: |
1. Go to '...'
2. Click on '....'
3. Scroll down to '....'
4. See error
validations:
required: true
- type: textarea
id: expected-behavior
attributes:
label: Expected behavior
description: A clear and concise description of what you expected to happen.
validations:
required: true
- type: textarea
id: screenshots-code
attributes:
label: Screenshots/Code snippets
description: If applicable, add screenshots or code snippets to help explain your problem.
validations:
required: true
- type: dropdown
id: os
attributes:
label: Operating System
description: Select the operating system you're using
options:
- Ubuntu 20.04
- Ubuntu 22.04
- Ubuntu 24.04
- macOS Catalina
- macOS Big Sur
- macOS Monterey
- macOS Ventura
- macOS Sonoma
- Windows 10
- Windows 11
- Other (specify in additional context)
validations:
required: true
- type: dropdown
id: python-version
attributes:
label: Python Version
description: Version of Python your Crew is running on
options:
- '3.10'
- '3.11'
- '3.12'
- '3.13'
validations:
required: true
- type: input
id: crewai-version
attributes:
label: crewAI Version
description: What version of CrewAI are you using
validations:
required: true
- type: input
id: crewai-tools-version
attributes:
label: crewAI Tools Version
description: What version of CrewAI Tools are you using
validations:
required: true
- type: dropdown
id: virtual-environment
attributes:
label: Virtual Environment
description: What Virtual Environment are you running your crew in.
options:
- Venv
- Conda
- Poetry
validations:
required: true
- type: textarea
id: evidence
attributes:
label: Evidence
description: Include relevant information, logs or error messages. These can be screenshots.
validations:
required: true
- type: textarea
id: possible-solution
attributes:
label: Possible Solution
description: Have a solution in mind? Please suggest it here, or write "None".
validations:
required: true
- type: textarea
id: additional-context
attributes:
label: Additional context
description: Add any other context about the problem here.
validations:
required: true

1
.github/ISSUE_TEMPLATE/config.yml vendored Normal file
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@@ -0,0 +1 @@
blank_issues_enabled: false

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@@ -1,24 +0,0 @@
---
name: Custom issue template
about: Describe this issue template's purpose here.
title: "[DOCS]"
labels: documentation
assignees: ''
---
## Documentation Page
<!-- Provide a link to the documentation page that needs improvement -->
## Description
<!-- Describe what needs to be changed or improved in the documentation -->
## Suggested Changes
<!-- If possible, provide specific suggestions for how to improve the documentation -->
## Additional Context
<!-- Add any other context about the documentation issue here -->
## Checklist
- [ ] I have searched the existing issues to make sure this is not a duplicate
- [ ] I have checked the latest version of the documentation to ensure this hasn't been addressed

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@@ -0,0 +1,65 @@
name: Feature request
description: Suggest a new feature for CrewAI
title: "[FEATURE]"
labels: ["feature-request"]
assignees: []
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this feature request!
- type: dropdown
id: feature-area
attributes:
label: Feature Area
description: Which area of CrewAI does this feature primarily relate to?
options:
- Core functionality
- Agent capabilities
- Task management
- Integration with external tools
- Performance optimization
- Documentation
- Other (please specify in additional context)
validations:
required: true
- type: textarea
id: problem
attributes:
label: Is your feature request related to a an existing bug? Please link it here.
description: A link to the bug or NA if not related to an existing bug.
validations:
required: true
- type: textarea
id: solution
attributes:
label: Describe the solution you'd like
description: A clear and concise description of what you want to happen.
validations:
required: true
- type: textarea
id: alternatives
attributes:
label: Describe alternatives you've considered
description: A clear and concise description of any alternative solutions or features you've considered.
validations:
required: false
- type: textarea
id: context
attributes:
label: Additional context
description: Add any other context, screenshots, or examples about the feature request here.
validations:
required: false
- type: dropdown
id: willingness-to-contribute
attributes:
label: Willingness to Contribute
description: Would you be willing to contribute to the implementation of this feature?
options:
- Yes, I'd be happy to submit a pull request
- I could provide more detailed specifications
- I can test the feature once it's implemented
- No, I'm just suggesting the idea
validations:
required: true

23
.github/workflows/security-checker.yml vendored Normal file
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@@ -0,0 +1,23 @@
name: Security Checker
on: [pull_request]
jobs:
security-check:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.11.9"
- name: Install dependencies
run: pip install bandit
- name: Run Bandit
run: bandit -c pyproject.toml -r src/ -lll

View File

@@ -0,0 +1,129 @@
# Creating a CrewAI Pipeline Project
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.
To learn more about CrewAI pipelines, visit the [CrewAI documentation](https://docs.crewai.com/core-concepts/Pipeline/).
## Prerequisites
Before getting started with CrewAI pipelines, make sure that you have installed CrewAI via pip:
```shell
$ pip install crewai crewai-tools
```
The same prerequisites for virtual environments and Code IDEs apply as in regular CrewAI projects.
## Creating a New Pipeline Project
To create a new CrewAI pipeline project, you have two options:
1. For a basic pipeline template:
```shell
$ crewai create pipeline <project_name>
```
2. For a pipeline example that includes a router:
```shell
$ crewai create pipeline --router <project_name>
```
These commands will create a new project folder with the following structure:
```
<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/
```
## Customizing Your Pipeline Project
To customize your pipeline project, you can:
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.
### Example: Defining a Pipeline
Here's an example of how to define a pipeline in `src/<project_name>/pipelines/normal_pipeline.py`:
```python
from crewai import Pipeline
from crewai.project import PipelineBase
from ..crews.normal_crew import NormalCrew
@PipelineBase
class NormalPipeline:
def __init__(self):
# Initialize crews
self.normal_crew = NormalCrew().crew()
def create_pipeline(self):
return Pipeline(
stages=[
self.normal_crew
]
)
async def kickoff(self, inputs):
pipeline = self.create_pipeline()
results = await pipeline.kickoff(inputs)
return results
```
### Annotations
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.
## Installing Dependencies
To install the dependencies for your project, use Poetry:
```shell
$ cd <project_name>
$ crewai install
```
## Running Your Pipeline Project
To run your pipeline project, use the following command:
```shell
$ crewai run
```
This will initialize your pipeline and begin task execution as defined in your `main.py` file.
## Deploying Your Pipeline Project
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.

View File

@@ -154,15 +154,15 @@ email_summarizer_task:
Use the annotations to properly reference the agent and task in the crew.py file.
### Annotations include:
* @agent
* @task
* @crew
* @llm
* @tool
* @callback
* @output_json
* @output_pydantic
* @cache_handler
* [@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
@@ -191,8 +191,7 @@ To install the dependencies for your project, you can use Poetry. First, navigat
```shell
$ cd my_project
$ poetry lock
$ poetry install
$ crewai install
```
This will install the dependencies specified in the `pyproject.toml` file.
@@ -233,11 +232,6 @@ To run your project, use the following command:
```shell
$ crewai run
```
or
```shell
$ poetry run my_project
```
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

View File

@@ -8,13 +8,20 @@ Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By
<div style="width:25%">
<h2>Getting Started</h2>
<ul>
<li><a href='./getting-started/Installing-CrewAI'>
<li>
<a href='./getting-started/Installing-CrewAI'>
Installing CrewAI
</a>
</a>
</li>
<li><a href='./getting-started/Start-a-New-CrewAI-Project-Template-Method'>
<li>
<a href='./getting-started/Start-a-New-CrewAI-Project-Template-Method'>
Start a New CrewAI Project: Template Method
</a>
</a>
</li>
<li>
<a href='./getting-started/Create-a-New-CrewAI-Pipeline-Template-Method'>
Create a New CrewAI Pipeline: Template Method
</a>
</li>
</ul>
</div>

View File

@@ -27,10 +27,10 @@ If needed you can also tweak the parameters of the DALL-E model by passing them
```python
from crewai_tools import DallETool
dalle_tool = DallETool(model: str = "dall-e-3",
size: str = "1024x1024",
quality: str = "standard",
n: int = 1)
dalle_tool = DallETool(model="dall-e-3",
size="1024x1024",
quality="standard",
n=1)
Agent(
...
@@ -38,4 +38,4 @@ Agent(
)
```
The parameter are based on the `client.images.generate` method from the OpenAI API. For more information on the parameters, please refer to the [OpenAI API documentation](https://platform.openai.com/docs/guides/images/introduction?lang=python).
The parameters are based on the `client.images.generate` method from the OpenAI API. For more information on the parameters, please refer to the [OpenAI API documentation](https://platform.openai.com/docs/guides/images/introduction?lang=python).

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@@ -0,0 +1,33 @@
# FileWriterTool Documentation
## Description
The `FileWriterTool` is a component of the crewai_tools package, designed to simplify the process of writing content to files. It is particularly useful in scenarios such as generating reports, saving logs, creating configuration files, and more. This tool supports creating new directories if they don't exist, making it easier to organize your output.
## Installation
Install the crewai_tools package to use the `FileWriterTool` in your projects:
```shell
pip install 'crewai[tools]'
```
## Example
To get started with the `FileWriterTool`:
```python
from crewai_tools import FileWriterTool
# Initialize the tool
file_writer_tool = FileWriterTool()
# Write content to a file in a specified directory
result = file_writer_tool._run('example.txt', 'This is a test content.', 'test_directory')
print(result)
```
## Arguments
- `filename`: The name of the file you want to create or overwrite.
- `content`: The content to write into the file.
- `directory` (optional): The path to the directory where the file will be created. Defaults to the current directory (`.`). If the directory does not exist, it will be created.
## Conclusion
By integrating the `FileWriterTool` into your crews, the agents can execute the process of writing content to files and creating directories. This tool is essential for tasks that require saving output data, creating structured file systems, and more. By adhering to the setup and usage guidelines provided, incorporating this tool into projects is straightforward and efficient.

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@@ -0,0 +1,42 @@
# FirecrawlCrawlWebsiteTool
## Description
[Firecrawl](https://firecrawl.dev) is a platform for crawling and convert any website into clean markdown or structured data.
## Installation
- Get an API key from [firecrawl.dev](https://firecrawl.dev) and set it in environment variables (`FIRECRAWL_API_KEY`).
- Install the [Firecrawl SDK](https://github.com/mendableai/firecrawl) along with `crewai[tools]` package:
```
pip install firecrawl-py 'crewai[tools]'
```
## Example
Utilize the FirecrawlScrapeFromWebsiteTool as follows to allow your agent to load websites:
```python
from crewai_tools import FirecrawlCrawlWebsiteTool
tool = FirecrawlCrawlWebsiteTool(url='firecrawl.dev')
```
## Arguments
- `api_key`: Optional. Specifies Firecrawl API key. Defaults is the `FIRECRAWL_API_KEY` environment variable.
- `url`: The base URL to start crawling from.
- `page_options`: Optional.
- `onlyMainContent`: Optional. Only return the main content of the page excluding headers, navs, footers, etc.
- `includeHtml`: Optional. Include the raw HTML content of the page. Will output a html key in the response.
- `crawler_options`: Optional. Options for controlling the crawling behavior.
- `includes`: Optional. URL patterns to include in the crawl.
- `exclude`: Optional. URL patterns to exclude from the crawl.
- `generateImgAltText`: Optional. Generate alt text for images using LLMs (requires a paid plan).
- `returnOnlyUrls`: Optional. If true, returns only the URLs as a list in the crawl status. Note: the response will be a list of URLs inside the data, not a list of documents.
- `maxDepth`: Optional. Maximum depth to crawl. Depth 1 is the base URL, depth 2 includes the base URL and its direct children, and so on.
- `mode`: Optional. The crawling mode to use. Fast mode crawls 4x faster on websites without a sitemap but may not be as accurate and shouldn't be used on heavily JavaScript-rendered websites.
- `limit`: Optional. Maximum number of pages to crawl.
- `timeout`: Optional. Timeout in milliseconds for the crawling operation.

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@@ -0,0 +1,38 @@
# FirecrawlScrapeWebsiteTool
## Description
[Firecrawl](https://firecrawl.dev) is a platform for crawling and convert any website into clean markdown or structured data.
## Installation
- Get an API key from [firecrawl.dev](https://firecrawl.dev) and set it in environment variables (`FIRECRAWL_API_KEY`).
- Install the [Firecrawl SDK](https://github.com/mendableai/firecrawl) along with `crewai[tools]` package:
```
pip install firecrawl-py 'crewai[tools]'
```
## Example
Utilize the FirecrawlScrapeWebsiteTool as follows to allow your agent to load websites:
```python
from crewai_tools import FirecrawlScrapeWebsiteTool
tool = FirecrawlScrapeWebsiteTool(url='firecrawl.dev')
```
## Arguments
- `api_key`: Optional. Specifies Firecrawl API key. Defaults is the `FIRECRAWL_API_KEY` environment variable.
- `url`: The URL to scrape.
- `page_options`: Optional.
- `onlyMainContent`: Optional. Only return the main content of the page excluding headers, navs, footers, etc.
- `includeHtml`: Optional. Include the raw HTML content of the page. Will output a html key in the response.
- `extractor_options`: Optional. Options for LLM-based extraction of structured information from the page content
- `mode`: The extraction mode to use, currently supports 'llm-extraction'
- `extractionPrompt`: Optional. A prompt describing what information to extract from the page
- `extractionSchema`: Optional. The schema for the data to be extracted
- `timeout`: Optional. Timeout in milliseconds for the request

View File

@@ -0,0 +1,35 @@
# FirecrawlSearchTool
## Description
[Firecrawl](https://firecrawl.dev) is a platform for crawling and convert any website into clean markdown or structured data.
## Installation
- Get an API key from [firecrawl.dev](https://firecrawl.dev) and set it in environment variables (`FIRECRAWL_API_KEY`).
- Install the [Firecrawl SDK](https://github.com/mendableai/firecrawl) along with `crewai[tools]` package:
```
pip install firecrawl-py 'crewai[tools]'
```
## Example
Utilize the FirecrawlSearchTool as follows to allow your agent to load websites:
```python
from crewai_tools import FirecrawlSearchTool
tool = FirecrawlSearchTool(query='what is firecrawl?')
```
## Arguments
- `api_key`: Optional. Specifies Firecrawl API key. Defaults is the `FIRECRAWL_API_KEY` environment variable.
- `query`: The search query string to be used for searching.
- `page_options`: Optional. Options for result formatting.
- `onlyMainContent`: Optional. Only return the main content of the page excluding headers, navs, footers, etc.
- `includeHtml`: Optional. Include the raw HTML content of the page. Will output a html key in the response.
- `fetchPageContent`: Optional. Fetch the full content of the page.
- `search_options`: Optional. Options for controlling the crawling behavior.
- `limit`: Optional. Maximum number of pages to crawl.

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@@ -47,8 +47,8 @@ The primary task goal was:
So the Agent tried to get information from the DB, the first one is wrong so the Agent tries again and gets the correct information and passes to the next agent.
![alt text](images/image-2.png)
![alt text](images/image-3.png)
![alt text](https://github.com/crewAIInc/crewAI-tools/blob/main/crewai_tools/tools/nl2sql/images/image-2.png?raw=true)
![alt text](https://github.com/crewAIInc/crewAI-tools/raw/main/crewai_tools/tools/nl2sql/images/image-3.png)
The second task goal was:
@@ -58,11 +58,11 @@ Include information on the average, maximum, and minimum monthly revenue for eac
Now things start to get interesting, the Agent generates the SQL query to not only create the table but also insert the data into the table. And in the end the Agent still returns the final report which is exactly what was in the database.
![alt text](images/image-4.png)
![alt text](images/image-5.png)
![alt text](https://github.com/crewAIInc/crewAI-tools/raw/main/crewai_tools/tools/nl2sql/images/image-4.png)
![alt text](https://github.com/crewAIInc/crewAI-tools/raw/main/crewai_tools/tools/nl2sql/images/image-5.png)
![alt text](images/image-9.png)
![alt text](images/image-7.png)
![alt text](https://github.com/crewAIInc/crewAI-tools/raw/main/crewai_tools/tools/nl2sql/images/image-9.png)
![alt text](https://github.com/crewAIInc/crewAI-tools/raw/main/crewai_tools/tools/nl2sql/images/image-7.png)
This is a simple example of how the NL2SQLTool can be used to interact with the database and generate reports based on the data in the database.

View File

@@ -129,6 +129,7 @@ nav:
- Processes: 'core-concepts/Processes.md'
- Crews: 'core-concepts/Crews.md'
- Collaboration: 'core-concepts/Collaboration.md'
- Pipeline: 'core-concepts/Pipeline.md'
- Training: 'core-concepts/Training-Crew.md'
- Memory: 'core-concepts/Memory.md'
- Planning: 'core-concepts/Planning.md'
@@ -152,33 +153,37 @@ nav:
- Agent Monitoring with AgentOps: 'how-to/AgentOps-Observability.md'
- Agent Monitoring with LangTrace: 'how-to/Langtrace-Observability.md'
- Tools Docs:
- Google Serper Search: 'tools/SerperDevTool.md'
- Browserbase Web Loader: 'tools/BrowserbaseLoadTool.md'
- Composio Tools: 'tools/ComposioTool.md'
- Code Docs RAG Search: 'tools/CodeDocsSearchTool.md'
- Code Interpreter: 'tools/CodeInterpreterTool.md'
- Scrape Website: 'tools/ScrapeWebsiteTool.md'
- Directory Read: 'tools/DirectoryReadTool.md'
- Exa Serch Web Loader: 'tools/EXASearchTool.md'
- File Read: 'tools/FileReadTool.md'
- Selenium Scraper: 'tools/SeleniumScrapingTool.md'
- Directory RAG Search: 'tools/DirectorySearchTool.md'
- DALL-E Tool: 'tools/DALL-ETool.md'
- PDF RAG Search: 'tools/PDFSearchTool.md'
- TXT RAG Search: 'tools/TXTSearchTool.md'
- Composio Tools: 'tools/ComposioTool.md'
- CSV RAG Search: 'tools/CSVSearchTool.md'
- XML RAG Search: 'tools/XMLSearchTool.md'
- JSON RAG Search: 'tools/JSONSearchTool.md'
- DALL-E Tool: 'tools/DALL-ETool.md'
- Directory RAG Search: 'tools/DirectorySearchTool.md'
- Directory Read: 'tools/DirectoryReadTool.md'
- Docx Rag Search: 'tools/DOCXSearchTool.md'
- EXA Serch Web Loader: 'tools/EXASearchTool.md'
- File Read: 'tools/FileReadTool.md'
- File Write: 'tools/FileWriteTool.md'
- Firecrawl Crawl Website Tool: 'tools/FirecrawlCrawlWebsiteTool.md'
- Firecrawl Scrape Website Tool: 'tools/FirecrawlScrapeWebsiteTool.md'
- Firecrawl Search Tool: 'tools/FirecrgstawlSearchTool.md'
- Github RAG Search: 'tools/GitHubSearchTool.md'
- Google Serper Search: 'tools/SerperDevTool.md'
- JSON RAG Search: 'tools/JSONSearchTool.md'
- MDX RAG Search: 'tools/MDXSearchTool.md'
- MySQL Tool: 'tools/MySQLTool.md'
- NL2SQL Tool: 'tools/NL2SQLTool.md'
- PDF RAG Search: 'tools/PDFSearchTool.md'
- PG RAG Search: 'tools/PGSearchTool.md'
- Scrape Website: 'tools/ScrapeWebsiteTool.md'
- Selenium Scraper: 'tools/SeleniumScrapingTool.md'
- TXT RAG Search: 'tools/TXTSearchTool.md'
- Vision Tool: 'tools/VisionTool.md'
- Website RAG Search: 'tools/WebsiteSearchTool.md'
- Github RAG Search: 'tools/GitHubSearchTool.md'
- Code Docs RAG Search: 'tools/CodeDocsSearchTool.md'
- Youtube Video RAG Search: 'tools/YoutubeVideoSearchTool.md'
- XML RAG Search: 'tools/XMLSearchTool.md'
- Youtube Channel RAG Search: 'tools/YoutubeChannelSearchTool.md'
- Youtube Video RAG Search: 'tools/YoutubeVideoSearchTool.md'
- Examples:
- Trip Planner Crew: https://github.com/joaomdmoura/crewAI-examples/tree/main/trip_planner"
- Create Instagram Post: https://github.com/joaomdmoura/crewAI-examples/tree/main/instagram_post"

61
poetry.lock generated
View File

@@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
[[package]]
name = "agentops"
@@ -829,29 +829,27 @@ name = "crewai-tools"
version = "0.8.3"
description = "Set of tools for the crewAI framework"
optional = false
python-versions = ">=3.10,<=3.13"
files = []
develop = false
python-versions = "<=3.13,>=3.10"
files = [
{file = "crewai_tools-0.8.3-py3-none-any.whl", hash = "sha256:a54a10c36b8403250e13d6594bd37db7e7deb3f9fabc77e8720c081864ae6189"},
{file = "crewai_tools-0.8.3.tar.gz", hash = "sha256:f0317ea1d926221b22fcf4b816d71916fe870aa66ed7ee2a0067dba42b5634eb"},
]
[package.dependencies]
beautifulsoup4 = "^4.12.3"
chromadb = "^0.4.22"
docker = "^7.1.0"
docx2txt = "^0.8"
embedchain = "^0.1.114"
lancedb = "^0.5.4"
beautifulsoup4 = ">=4.12.3,<5.0.0"
chromadb = ">=0.4.22,<0.5.0"
docker = ">=7.1.0,<8.0.0"
docx2txt = ">=0.8,<0.9"
embedchain = ">=0.1.114,<0.2.0"
lancedb = ">=0.5.4,<0.6.0"
langchain = ">0.2,<=0.3"
openai = "^1.12.0"
pydantic = "^2.6.1"
pyright = "^1.1.350"
pytest = "^8.0.0"
pytube = "^15.0.0"
requests = "^2.31.0"
selenium = "^4.18.1"
[package.source]
type = "directory"
url = "../crewai-tools"
openai = ">=1.12.0,<2.0.0"
pydantic = ">=2.6.1,<3.0.0"
pyright = ">=1.1.350,<2.0.0"
pytest = ">=8.0.0,<9.0.0"
pytube = ">=15.0.0,<16.0.0"
requests = ">=2.31.0,<3.0.0"
selenium = ">=4.18.1,<5.0.0"
[[package]]
name = "cssselect2"
@@ -1321,12 +1319,12 @@ files = [
google-auth = ">=2.14.1,<3.0.dev0"
googleapis-common-protos = ">=1.56.2,<2.0.dev0"
grpcio = [
{version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
{version = ">=1.33.2,<2.0dev", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
{version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
]
grpcio-status = [
{version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
{version = ">=1.33.2,<2.0.dev0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
{version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
]
proto-plus = ">=1.22.3,<2.0.0dev"
protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
@@ -3628,8 +3626,8 @@ files = [
[package.dependencies]
numpy = [
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
{version = ">=1.22.4", markers = "python_version < \"3.11\""},
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
]
python-dateutil = ">=2.8.2"
@@ -4027,6 +4025,19 @@ files = [
{file = "pyarrow-17.0.0-cp312-cp312-win_amd64.whl", hash = "sha256:392bc9feabc647338e6c89267635e111d71edad5fcffba204425a7c8d13610d7"},
{file = "pyarrow-17.0.0-cp38-cp38-macosx_10_15_x86_64.whl", hash = "sha256:af5ff82a04b2171415f1410cff7ebb79861afc5dae50be73ce06d6e870615204"},
{file = "pyarrow-17.0.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:edca18eaca89cd6382dfbcff3dd2d87633433043650c07375d095cd3517561d8"},
{file = "pyarrow-17.0.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7c7916bff914ac5d4a8fe25b7a25e432ff921e72f6f2b7547d1e325c1ad9d155"},
{file = "pyarrow-17.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f553ca691b9e94b202ff741bdd40f6ccb70cdd5fbf65c187af132f1317de6145"},
{file = "pyarrow-17.0.0-cp38-cp38-manylinux_2_28_aarch64.whl", hash = "sha256:0cdb0e627c86c373205a2f94a510ac4376fdc523f8bb36beab2e7f204416163c"},
{file = "pyarrow-17.0.0-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:d7d192305d9d8bc9082d10f361fc70a73590a4c65cf31c3e6926cd72b76bc35c"},
{file = "pyarrow-17.0.0-cp38-cp38-win_amd64.whl", hash = "sha256:02dae06ce212d8b3244dd3e7d12d9c4d3046945a5933d28026598e9dbbda1fca"},
{file = "pyarrow-17.0.0-cp39-cp39-macosx_10_15_x86_64.whl", hash = "sha256:13d7a460b412f31e4c0efa1148e1d29bdf18ad1411eb6757d38f8fbdcc8645fb"},
{file = "pyarrow-17.0.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:9b564a51fbccfab5a04a80453e5ac6c9954a9c5ef2890d1bcf63741909c3f8df"},
{file = "pyarrow-17.0.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:32503827abbc5aadedfa235f5ece8c4f8f8b0a3cf01066bc8d29de7539532687"},
{file = "pyarrow-17.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a155acc7f154b9ffcc85497509bcd0d43efb80d6f733b0dc3bb14e281f131c8b"},
{file = "pyarrow-17.0.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:dec8d129254d0188a49f8a1fc99e0560dc1b85f60af729f47de4046015f9b0a5"},
{file = "pyarrow-17.0.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:a48ddf5c3c6a6c505904545c25a4ae13646ae1f8ba703c4df4a1bfe4f4006bda"},
{file = "pyarrow-17.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:42bf93249a083aca230ba7e2786c5f673507fa97bbd9725a1e2754715151a204"},
{file = "pyarrow-17.0.0.tar.gz", hash = "sha256:4beca9521ed2c0921c1023e68d097d0299b62c362639ea315572a58f3f50fd28"},
]
[package.dependencies]
@@ -6062,4 +6073,4 @@ tools = ["crewai-tools"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.10,<=3.13"
content-hash = "fc1b510ea9c814db67ac69d2454071b718cb7f6846bd845f7f48561cb0397ce1"
content-hash = "91ba982ea96ca7be017d536784223d4ef83e86de05d11eb1c3ce0fc1b726f283"

View File

@@ -1,6 +1,6 @@
[tool.poetry]
name = "crewai"
version = "0.51.0"
version = "0.51.1"
description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
authors = ["Joao Moura <joao@crewai.com>"]
readme = "README.md"
@@ -62,6 +62,9 @@ ignore_missing_imports = true
disable_error_code = 'import-untyped'
exclude = ["cli/templates"]
[tool.bandit]
exclude_dirs = ["src/crewai/cli/templates"]
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

View File

@@ -113,10 +113,11 @@ class Agent(BaseAgent):
description="Maximum number of retries for an agent to execute a task when an error occurs.",
)
def __init__(__pydantic_self__, **data):
config = data.pop("config", {})
super().__init__(**config, **data)
__pydantic_self__.agent_ops_agent_name = __pydantic_self__.role
@model_validator(mode="after")
def set_agent_ops_agent_name(self) -> "Agent":
"""Set agent ops agent name."""
self.agent_ops_agent_name = self.role
return self
@model_validator(mode="after")
def set_agent_executor(self) -> "Agent":
@@ -213,7 +214,7 @@ class Agent(BaseAgent):
raise e
result = self.execute_task(task, context, tools)
if self.max_rpm:
if self.max_rpm and self._rpm_controller:
self._rpm_controller.stop_rpm_counter()
# If there was any tool in self.tools_results that had result_as_answer

View File

@@ -7,7 +7,6 @@ from typing import Any, Dict, List, Optional, TypeVar
from pydantic import (
UUID4,
BaseModel,
ConfigDict,
Field,
InstanceOf,
PrivateAttr,
@@ -74,12 +73,17 @@ class BaseAgent(ABC, BaseModel):
"""
__hash__ = object.__hash__ # type: ignore
_logger: Logger = PrivateAttr()
_rpm_controller: RPMController = PrivateAttr(default=None)
_logger: Logger = PrivateAttr(default_factory=lambda: Logger(verbose=False))
_rpm_controller: Optional[RPMController] = PrivateAttr(default=None)
_request_within_rpm_limit: Any = PrivateAttr(default=None)
formatting_errors: int = 0
model_config = ConfigDict(arbitrary_types_allowed=True)
_original_role: Optional[str] = PrivateAttr(default=None)
_original_goal: Optional[str] = PrivateAttr(default=None)
_original_backstory: Optional[str] = PrivateAttr(default=None)
_token_process: TokenProcess = PrivateAttr(default_factory=TokenProcess)
id: UUID4 = Field(default_factory=uuid.uuid4, frozen=True)
formatting_errors: int = Field(
default=0, description="Number of formatting errors."
)
role: str = Field(description="Role of the agent")
goal: str = Field(description="Objective of the agent")
backstory: str = Field(description="Backstory of the agent")
@@ -123,15 +127,6 @@ class BaseAgent(ABC, BaseModel):
default=None, description="Maximum number of tokens for the agent's execution."
)
_original_role: str | None = None
_original_goal: str | None = None
_original_backstory: str | None = None
_token_process: TokenProcess = TokenProcess()
def __init__(__pydantic_self__, **data):
config = data.pop("config", {})
super().__init__(**config, **data)
@model_validator(mode="after")
def set_config_attributes(self):
if self.config:
@@ -170,7 +165,7 @@ class BaseAgent(ABC, BaseModel):
@property
def key(self):
source = [self.role, self.goal, self.backstory]
return md5("|".join(source).encode()).hexdigest()
return md5("|".join(source).encode(), usedforsecurity=False).hexdigest()
@abstractmethod
def execute_task(

View File

@@ -1,13 +1,12 @@
from typing import Optional
from typing import Any, Dict, Optional
from pydantic import BaseModel, PrivateAttr
class CacheHandler:
class CacheHandler(BaseModel):
"""Callback handler for tool usage."""
_cache: dict = {}
def __init__(self):
self._cache = {}
_cache: Dict[str, Any] = PrivateAttr(default_factory=dict)
def add(self, tool, input, output):
self._cache[f"{tool}-{input}"] = output

View File

@@ -1,33 +1,29 @@
import threading
import time
from typing import Any, Dict, Iterator, List, Literal, Optional, Tuple, Union
import click
from langchain.agents import AgentExecutor
from langchain.agents.agent import ExceptionTool
from langchain.callbacks.manager import CallbackManagerForChainRun
from langchain.chains.summarize import load_summarize_chain
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_core.agents import AgentAction, AgentFinish, AgentStep
from langchain_core.exceptions import OutputParserException
from langchain_core.tools import BaseTool
from langchain_core.utils.input import get_color_mapping
from pydantic import InstanceOf
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.chains.summarize import load_summarize_chain
from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
from crewai.agents.tools_handler import ToolsHandler
from crewai.tools.tool_usage import ToolUsage, ToolUsageErrorException
from crewai.utilities import I18N
from crewai.utilities.constants import TRAINING_DATA_FILE
from crewai.utilities.exceptions.context_window_exceeding_exception import (
LLMContextLengthExceededException,
)
from crewai.utilities.training_handler import CrewTrainingHandler
from crewai.utilities.logger import Logger
from crewai.utilities.training_handler import CrewTrainingHandler
class CrewAgentExecutor(AgentExecutor, CrewAgentExecutorMixin):
@@ -213,11 +209,7 @@ class CrewAgentExecutor(AgentExecutor, CrewAgentExecutorMixin):
yield step
return
yield AgentStep(
action=AgentAction("_Exception", str(e), str(e)),
observation=str(e),
)
return
raise e
# If the tool chosen is the finishing tool, then we end and return.
if isinstance(output, AgentFinish):

View File

@@ -8,6 +8,7 @@ from crewai.memory.storage.kickoff_task_outputs_storage import (
)
from .evaluate_crew import evaluate_crew
from .install_crew import install_crew
from .replay_from_task import replay_task_command
from .reset_memories_command import reset_memories_command
from .run_crew import run_crew
@@ -165,10 +166,16 @@ def test(n_iterations: int, model: str):
evaluate_crew(n_iterations, model)
@crewai.command()
def install():
"""Install the Crew."""
install_crew()
@crewai.command()
def run():
"""Run the crew."""
click.echo("Running the crew")
"""Run the Crew."""
click.echo("Running the Crew")
run_crew()

View File

@@ -0,0 +1,21 @@
import subprocess
import click
def install_crew() -> None:
"""
Install the crew by running the Poetry command to lock and install.
"""
try:
subprocess.run(["poetry", "lock"], check=True, capture_output=False, text=True)
subprocess.run(
["poetry", "install"], check=True, capture_output=False, text=True
)
except subprocess.CalledProcessError as e:
click.echo(f"An error occurred while running the crew: {e}", err=True)
click.echo(e.output, err=True)
except Exception as e:
click.echo(f"An unexpected error occurred: {e}", err=True)

View File

@@ -14,12 +14,9 @@ pip install poetry
Next, navigate to your project directory and install the dependencies:
1. First lock the dependencies and then install them:
1. First lock the dependencies and install them by using the CLI command:
```bash
poetry lock
```
```bash
poetry install
crewai install
```
### Customizing
@@ -37,10 +34,6 @@ To kickstart your crew of AI agents and begin task execution, run this from the
```bash
$ crewai run
```
or
```bash
poetry run {{folder_name}}
```
This command initializes the {{name}} Crew, assembling the agents and assigning them tasks as defined in your configuration.

View File

@@ -6,7 +6,8 @@ authors = ["Your Name <you@example.com>"]
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
crewai = { extras = ["tools"], version = "^0.51.0" }
crewai = { extras = ["tools"], version = ">=0.51.0,<1.0.0" }
[tool.poetry.scripts]
{{folder_name}} = "{{folder_name}}.main:run"

View File

@@ -15,12 +15,11 @@ pip install poetry
Next, navigate to your project directory and install the dependencies:
1. First lock the dependencies and then install them:
```bash
poetry lock
```
```bash
poetry install
crewai install
```
### Customizing
**Add your `OPENAI_API_KEY` into the `.env` file**
@@ -35,7 +34,7 @@ poetry install
To kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:
```bash
poetry run {{folder_name}}
crewai run
```
This command initializes the {{name}} Crew, assembling the agents and assigning them tasks as defined in your configuration.
@@ -49,6 +48,7 @@ The {{name}} Crew is composed of multiple AI agents, each with unique roles, goa
## Support
For support, questions, or feedback regarding the {{crew_name}} Crew or crewAI.
- Visit our [documentation](https://docs.crewai.com)
- Reach out to us through our [GitHub repository](https://github.com/joaomdmoura/crewai)
- [Join our Discord](https://discord.com/invite/X4JWnZnxPb)

View File

@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
crewai = { extras = ["tools"], version = "^0.51.0" }
crewai = { extras = ["tools"], version = ">=0.51.0,<1.0.0" }
asyncio = "*"
[tool.poetry.scripts]

View File

@@ -16,10 +16,7 @@ Next, navigate to your project directory and install the dependencies:
1. First lock the dependencies and then install them:
```bash
poetry lock
```
```bash
poetry install
crewai install
```
### Customizing
@@ -35,7 +32,7 @@ poetry install
To kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:
```bash
poetry run {{folder_name}}
crewai run
```
This command initializes the {{name}} Crew, assembling the agents and assigning them tasks as defined in your configuration.

View File

@@ -6,7 +6,8 @@ authors = ["Your Name <you@example.com>"]
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
crewai = { extras = ["tools"], version = "^0.51.0" }
crewai = { extras = ["tools"], version = ">=0.51.0,<1.0.0" }
[tool.poetry.scripts]
{{folder_name}} = "{{folder_name}}.main:main"

View File

@@ -1,16 +1,15 @@
import asyncio
import json
import os
import uuid
from concurrent.futures import Future
from hashlib import md5
import os
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
from langchain_core.callbacks import BaseCallbackHandler
from pydantic import (
UUID4,
BaseModel,
ConfigDict,
Field,
InstanceOf,
Json,
@@ -48,11 +47,10 @@ from crewai.utilities.planning_handler import CrewPlanner
from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
from crewai.utilities.training_handler import CrewTrainingHandler
agentops = None
if os.environ.get("AGENTOPS_API_KEY"):
try:
import agentops
import agentops # type: ignore
except ImportError:
pass
@@ -106,7 +104,6 @@ class Crew(BaseModel):
name: Optional[str] = Field(default=None)
cache: bool = Field(default=True)
model_config = ConfigDict(arbitrary_types_allowed=True)
tasks: List[Task] = Field(default_factory=list)
agents: List[BaseAgent] = Field(default_factory=list)
process: Process = Field(default=Process.sequential)
@@ -364,7 +361,7 @@ class Crew(BaseModel):
source = [agent.key for agent in self.agents] + [
task.key for task in self.tasks
]
return md5("|".join(source).encode()).hexdigest()
return md5("|".join(source).encode(), usedforsecurity=False).hexdigest()
def _setup_from_config(self):
assert self.config is not None, "Config should not be None."
@@ -541,7 +538,7 @@ class Crew(BaseModel):
)._handle_crew_planning()
for task, step_plan in zip(self.tasks, result.list_of_plans_per_task):
task.description += step_plan
task.description += step_plan.plan
def _store_execution_log(
self,

View File

@@ -6,12 +6,20 @@ def task(func):
task.registration_order = []
func.is_task = True
wrapped_func = memoize(func)
memoized_func = memoize(func)
# Append the function name to the registration order list
task.registration_order.append(func.__name__)
return wrapped_func
def wrapper(*args, **kwargs):
result = memoized_func(*args, **kwargs)
if not result.name:
result.name = func.__name__
return result
return wrapper
def agent(func):

View File

@@ -1,56 +1,45 @@
import inspect
import os
from pathlib import Path
from typing import Any, Callable, Dict
import yaml
from dotenv import load_dotenv
from pydantic import ConfigDict
load_dotenv()
def CrewBase(cls):
class WrappedClass(cls):
model_config = ConfigDict(arbitrary_types_allowed=True)
is_crew_class: bool = True # type: ignore
base_directory = None
for frame_info in inspect.stack():
if "site-packages" not in frame_info.filename:
base_directory = Path(frame_info.filename).parent.resolve()
break
# Get the directory of the class being decorated
base_directory = Path(inspect.getfile(cls)).parent
original_agents_config_path = getattr(
cls, "agents_config", "config/agents.yaml"
)
original_tasks_config_path = getattr(cls, "tasks_config", "config/tasks.yaml")
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
if self.base_directory is None:
raise Exception(
"Unable to dynamically determine the project's base directory, you must run it from the project's root directory."
)
agents_config_path = self.base_directory / self.original_agents_config_path
tasks_config_path = self.base_directory / self.original_tasks_config_path
self.agents_config = self.load_yaml(
os.path.join(self.base_directory, self.original_agents_config_path)
)
self.tasks_config = self.load_yaml(
os.path.join(self.base_directory, self.original_tasks_config_path)
)
self.agents_config = self.load_yaml(agents_config_path)
self.tasks_config = self.load_yaml(tasks_config_path)
self.map_all_agent_variables()
self.map_all_task_variables()
@staticmethod
def load_yaml(config_path: str):
with open(config_path, "r") as file:
# parsedContent = YamlParser.parse(file) # type: ignore # Argument 1 to "parse" has incompatible type "TextIOWrapper"; expected "YamlParser"
return yaml.safe_load(file)
def load_yaml(config_path: Path):
try:
with open(config_path, "r") as file:
return yaml.safe_load(file)
except FileNotFoundError:
print(f"File not found: {config_path}")
raise
def _get_all_functions(self):
return {

View File

@@ -1,24 +1,24 @@
from typing import Callable, Dict
from pydantic import ConfigDict
from typing import Any, Callable, Dict, List, Type, Union
from crewai.crew import Crew
from crewai.pipeline.pipeline import Pipeline
from crewai.routers.router import Router
PipelineStage = Union[Crew, List[Crew], Router]
# TODO: Could potentially remove. Need to check with @joao and @gui if this is needed for CrewAI+
def PipelineBase(cls):
def PipelineBase(cls: Type[Any]) -> Type[Any]:
class WrappedClass(cls):
model_config = ConfigDict(arbitrary_types_allowed=True)
is_pipeline_class: bool = True
is_pipeline_class: bool = True # type: ignore
stages: List[PipelineStage]
def __init__(self, *args, **kwargs):
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
self.stages = []
self._map_pipeline_components()
def _get_all_functions(self):
def _get_all_functions(self) -> Dict[str, Callable[..., Any]]:
return {
name: getattr(self, name)
for name in dir(self)
@@ -26,15 +26,15 @@ def PipelineBase(cls):
}
def _filter_functions(
self, functions: Dict[str, Callable], attribute: str
) -> Dict[str, Callable]:
self, functions: Dict[str, Callable[..., Any]], attribute: str
) -> Dict[str, Callable[..., Any]]:
return {
name: func
for name, func in functions.items()
if hasattr(func, attribute)
}
def _map_pipeline_components(self):
def _map_pipeline_components(self) -> None:
all_functions = self._get_all_functions()
crew_functions = self._filter_functions(all_functions, "is_crew")
router_functions = self._filter_functions(all_functions, "is_router")

View File

@@ -1,32 +1,26 @@
from copy import deepcopy
from typing import Any, Callable, Dict, Generic, Tuple, TypeVar
from typing import Any, Callable, Dict, Tuple
from pydantic import BaseModel, Field, PrivateAttr
T = TypeVar("T", bound=Dict[str, Any])
U = TypeVar("U")
class Route(BaseModel):
condition: Callable[[Dict[str, Any]], bool]
pipeline: Any
class Route(Generic[T, U]):
condition: Callable[[T], bool]
pipeline: U
def __init__(self, condition: Callable[[T], bool], pipeline: U):
self.condition = condition
self.pipeline = pipeline
class Router(BaseModel, Generic[T, U]):
routes: Dict[str, Route[T, U]] = Field(
class Router(BaseModel):
routes: Dict[str, Route] = Field(
default_factory=dict,
description="Dictionary of route names to (condition, pipeline) tuples",
)
default: U = Field(..., description="Default pipeline if no conditions are met")
default: Any = Field(..., description="Default pipeline if no conditions are met")
_route_types: Dict[str, type] = PrivateAttr(default_factory=dict)
model_config = {"arbitrary_types_allowed": True}
class Config:
arbitrary_types_allowed = True
def __init__(self, routes: Dict[str, Route[T, U]], default: U, **data):
def __init__(self, routes: Dict[str, Route], default: Any, **data):
super().__init__(routes=routes, default=default, **data)
self._check_copyable(default)
for name, route in routes.items():
@@ -34,16 +28,16 @@ class Router(BaseModel, Generic[T, U]):
self._route_types[name] = type(route.pipeline)
@staticmethod
def _check_copyable(obj):
def _check_copyable(obj: Any) -> None:
if not hasattr(obj, "copy") or not callable(getattr(obj, "copy")):
raise ValueError(f"Object of type {type(obj)} must have a 'copy' method")
def add_route(
self,
name: str,
condition: Callable[[T], bool],
pipeline: U,
) -> "Router[T, U]":
condition: Callable[[Dict[str, Any]], bool],
pipeline: Any,
) -> "Router":
"""
Add a named route with its condition and corresponding pipeline to the router.
@@ -60,7 +54,7 @@ class Router(BaseModel, Generic[T, U]):
self._route_types[name] = type(pipeline)
return self
def route(self, input_data: T) -> Tuple[U, str]:
def route(self, input_data: Dict[str, Any]) -> Tuple[Any, str]:
"""
Evaluate the input against the conditions and return the appropriate pipeline.
@@ -76,15 +70,15 @@ class Router(BaseModel, Generic[T, U]):
return self.default, "default"
def copy(self) -> "Router[T, U]":
def copy(self) -> "Router":
"""Create a deep copy of the Router."""
new_routes = {
name: Route(
condition=deepcopy(route.condition),
pipeline=route.pipeline.copy(), # type: ignore
pipeline=route.pipeline.copy(),
)
for name, route in self.routes.items()
}
new_default = self.default.copy() # type: ignore
new_default = self.default.copy()
return Router(routes=new_routes, default=new_default)

View File

@@ -9,7 +9,14 @@ from hashlib import md5
from typing import Any, Dict, List, Optional, Tuple, Type, Union
from opentelemetry.trace import Span
from pydantic import UUID4, BaseModel, Field, field_validator, model_validator
from pydantic import (
UUID4,
BaseModel,
Field,
PrivateAttr,
field_validator,
model_validator,
)
from pydantic_core import PydanticCustomError
from crewai.agents.agent_builder.base_agent import BaseAgent
@@ -39,9 +46,6 @@ class Task(BaseModel):
tools: List of tools/resources limited for task execution.
"""
class Config:
arbitrary_types_allowed = True
__hash__ = object.__hash__ # type: ignore
used_tools: int = 0
tools_errors: int = 0
@@ -104,16 +108,12 @@ class Task(BaseModel):
default=None,
)
_telemetry: Telemetry
_execution_span: Span | None = None
_original_description: str | None = None
_original_expected_output: str | None = None
_thread: threading.Thread | None = None
_execution_time: float | None = None
def __init__(__pydantic_self__, **data):
config = data.pop("config", {})
super().__init__(**config, **data)
_telemetry: Telemetry = PrivateAttr(default_factory=Telemetry)
_execution_span: Optional[Span] = PrivateAttr(default=None)
_original_description: Optional[str] = PrivateAttr(default=None)
_original_expected_output: Optional[str] = PrivateAttr(default=None)
_thread: Optional[threading.Thread] = PrivateAttr(default=None)
_execution_time: Optional[float] = PrivateAttr(default=None)
@field_validator("id", mode="before")
@classmethod
@@ -137,12 +137,6 @@ class Task(BaseModel):
return value[1:]
return value
@model_validator(mode="after")
def set_private_attrs(self) -> "Task":
"""Set private attributes."""
self._telemetry = Telemetry()
return self
@model_validator(mode="after")
def set_attributes_based_on_config(self) -> "Task":
"""Set attributes based on the agent configuration."""
@@ -185,7 +179,7 @@ class Task(BaseModel):
expected_output = self._original_expected_output or self.expected_output
source = [description, expected_output]
return md5("|".join(source).encode()).hexdigest()
return md5("|".join(source).encode(), usedforsecurity=False).hexdigest()
def execute_async(
self,
@@ -240,7 +234,9 @@ class Task(BaseModel):
pydantic_output, json_output = self._export_output(result)
task_output = TaskOutput(
name=self.name,
description=self.description,
expected_output=self.expected_output,
raw=result,
pydantic=pydantic_output,
json_dict=json_output,
@@ -261,9 +257,7 @@ class Task(BaseModel):
content = (
json_output
if json_output
else pydantic_output.model_dump_json()
if pydantic_output
else result
else pydantic_output.model_dump_json() if pydantic_output else result
)
self._save_file(content)

View File

@@ -10,6 +10,10 @@ class TaskOutput(BaseModel):
"""Class that represents the result of a task."""
description: str = Field(description="Description of the task")
name: Optional[str] = Field(description="Name of the task", default=None)
expected_output: Optional[str] = Field(
description="Expected output of the task", default=None
)
summary: Optional[str] = Field(description="Summary of the task", default=None)
raw: str = Field(description="Raw output of the task", default="")
pydantic: Optional[BaseModel] = Field(

View File

@@ -98,65 +98,70 @@ class Telemetry:
self._add_attribute(span, "crew_memory", crew.memory)
self._add_attribute(span, "crew_number_of_tasks", len(crew.tasks))
self._add_attribute(span, "crew_number_of_agents", len(crew.agents))
self._add_attribute(
span,
"crew_agents",
json.dumps(
[
{
"key": agent.key,
"id": str(agent.id),
"role": agent.role,
"goal": agent.goal,
"backstory": agent.backstory,
"verbose?": agent.verbose,
"max_iter": agent.max_iter,
"max_rpm": agent.max_rpm,
"i18n": agent.i18n.prompt_file,
"llm": json.dumps(self._safe_llm_attributes(agent.llm)),
"delegation_enabled?": agent.allow_delegation,
"tools_names": [
tool.name.casefold() for tool in agent.tools or []
],
}
for agent in crew.agents
]
),
)
self._add_attribute(
span,
"crew_tasks",
json.dumps(
[
{
"key": task.key,
"id": str(task.id),
"description": task.description,
"expected_output": task.expected_output,
"async_execution?": task.async_execution,
"human_input?": task.human_input,
"agent_role": task.agent.role if task.agent else "None",
"agent_key": task.agent.key if task.agent else None,
"context": (
[task.description for task in task.context]
if task.context
else None
),
"tools_names": [
tool.name.casefold() for tool in task.tools or []
],
}
for task in crew.tasks
]
),
)
self._add_attribute(span, "platform", platform.platform())
self._add_attribute(span, "platform_release", platform.release())
self._add_attribute(span, "platform_system", platform.system())
self._add_attribute(span, "platform_version", platform.version())
self._add_attribute(span, "cpus", os.cpu_count())
if crew.share_crew:
self._add_attribute(
span,
"crew_agents",
json.dumps(
[
{
"key": agent.key,
"id": str(agent.id),
"role": agent.role,
"goal": agent.goal,
"backstory": agent.backstory,
"verbose?": agent.verbose,
"max_iter": agent.max_iter,
"max_rpm": agent.max_rpm,
"i18n": agent.i18n.prompt_file,
"llm": json.dumps(
self._safe_llm_attributes(agent.llm)
),
"delegation_enabled?": agent.allow_delegation,
"tools_names": [
tool.name.casefold()
for tool in agent.tools or []
],
}
for agent in crew.agents
]
),
)
self._add_attribute(
span,
"crew_tasks",
json.dumps(
[
{
"key": task.key,
"id": str(task.id),
"description": task.description,
"expected_output": task.expected_output,
"async_execution?": task.async_execution,
"human_input?": task.human_input,
"agent_role": task.agent.role
if task.agent
else "None",
"agent_key": task.agent.key if task.agent else None,
"context": (
[task.description for task in task.context]
if task.context
else None
),
"tools_names": [
tool.name.casefold()
for tool in task.tools or []
],
}
for task in crew.tasks
]
),
)
self._add_attribute(span, "platform", platform.platform())
self._add_attribute(span, "platform_release", platform.release())
self._add_attribute(span, "platform_system", platform.system())
self._add_attribute(span, "platform_version", platform.version())
self._add_attribute(span, "cpus", os.cpu_count())
self._add_attribute(
span, "crew_inputs", json.dumps(inputs) if inputs else None
)
@@ -290,7 +295,7 @@ class Telemetry:
pass
def individual_test_result_span(
self, crew: Crew, quality: int, exec_time: int, model_name: str
self, crew: Crew, quality: float, exec_time: int, model_name: str
):
if self.ready:
try:

View File

@@ -1,5 +1,5 @@
from langchain.tools import StructuredTool
from pydantic import BaseModel, ConfigDict, Field
from pydantic import BaseModel, Field
from crewai.agents.cache import CacheHandler
@@ -7,11 +7,10 @@ from crewai.agents.cache import CacheHandler
class CacheTools(BaseModel):
"""Default tools to hit the cache."""
model_config = ConfigDict(arbitrary_types_allowed=True)
name: str = "Hit Cache"
cache_handler: CacheHandler = Field(
description="Cache Handler for the crew",
default=CacheHandler(),
default_factory=CacheHandler,
)
def tool(self):

View File

@@ -1,6 +1,6 @@
import ast
from difflib import SequenceMatcher
import os
from difflib import SequenceMatcher
from textwrap import dedent
from typing import Any, List, Union
@@ -15,7 +15,7 @@ from crewai.utilities import I18N, Converter, ConverterError, Printer
agentops = None
if os.environ.get("AGENTOPS_API_KEY"):
try:
import agentops
import agentops # type: ignore
except ImportError:
pass
@@ -71,14 +71,14 @@ class ToolUsage:
self.task = task
self.action = action
self.function_calling_llm = function_calling_llm
# Handling bug (see https://github.com/langchain-ai/langchain/pull/16395): raise an error if tools_names have space for ChatOpenAI
if isinstance(self.function_calling_llm, ChatOpenAI):
if " " in self.tools_names:
raise Exception(
"Tools names should not have spaces for ChatOpenAI models."
)
# Set the maximum parsing attempts for bigger models
if (isinstance(self.function_calling_llm, ChatOpenAI)) and (
self.function_calling_llm.openai_api_base is None
@@ -118,7 +118,7 @@ class ToolUsage:
tool: BaseTool,
calling: Union[ToolCalling, InstructorToolCalling],
) -> str: # TODO: Fix this return type
tool_event = agentops.ToolEvent(name=calling.tool_name) if agentops else None
tool_event = agentops.ToolEvent(name=calling.tool_name) if agentops else None # type: ignore
if self._check_tool_repeated_usage(calling=calling): # type: ignore # _check_tool_repeated_usage of "ToolUsage" does not return a value (it only ever returns None)
try:
result = self._i18n.errors("task_repeated_usage").format(

View File

@@ -1,13 +1,13 @@
from datetime import datetime
from pydantic import BaseModel, Field, PrivateAttr
from crewai.utilities.printer import Printer
class Logger:
_printer = Printer()
def __init__(self, verbose=False):
self.verbose = verbose
class Logger(BaseModel):
verbose: bool = Field(default=False)
_printer: Printer = PrivateAttr(default_factory=Printer)
def log(self, level, message, color="bold_green"):
if self.verbose:

View File

@@ -1,14 +1,25 @@
from typing import Any, List, Optional
from langchain_openai import ChatOpenAI
from pydantic import BaseModel
from pydantic import BaseModel, Field
from crewai.agent import Agent
from crewai.task import Task
class PlanPerTask(BaseModel):
task: str = Field(..., description="The task for which the plan is created")
plan: str = Field(
...,
description="The step by step plan on how the agents can execute their tasks using the available tools with mastery",
)
class PlannerTaskPydanticOutput(BaseModel):
list_of_plans_per_task: List[str]
list_of_plans_per_task: List[PlanPerTask] = Field(
...,
description="Step by step plan on how the agents can execute their tasks using the available tools with mastery",
)
class CrewPlanner:

View File

@@ -1,44 +1,50 @@
import threading
import time
from typing import Union
from typing import Optional
from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, model_validator
from pydantic import BaseModel, Field, PrivateAttr, model_validator
from crewai.utilities.logger import Logger
class RPMController(BaseModel):
model_config = ConfigDict(arbitrary_types_allowed=True)
max_rpm: Union[int, None] = Field(default=None)
logger: Logger = Field(default=None)
max_rpm: Optional[int] = Field(default=None)
logger: Logger = Field(default_factory=lambda: Logger(verbose=False))
_current_rpm: int = PrivateAttr(default=0)
_timer: threading.Timer | None = PrivateAttr(default=None)
_lock: threading.Lock = PrivateAttr(default=None)
_shutdown_flag = False
_timer: Optional[threading.Timer] = PrivateAttr(default=None)
_lock: Optional[threading.Lock] = PrivateAttr(default=None)
_shutdown_flag: bool = PrivateAttr(default=False)
@model_validator(mode="after")
def reset_counter(self):
if self.max_rpm:
if self.max_rpm is not None:
if not self._shutdown_flag:
self._lock = threading.Lock()
self._reset_request_count()
return self
def check_or_wait(self):
if not self.max_rpm:
if self.max_rpm is None:
return True
with self._lock:
if self._current_rpm < self.max_rpm:
def _check_and_increment():
if self.max_rpm is not None and self._current_rpm < self.max_rpm:
self._current_rpm += 1
return True
else:
elif self.max_rpm is not None:
self.logger.log(
"info", "Max RPM reached, waiting for next minute to start."
)
self._wait_for_next_minute()
self._current_rpm = 1
return True
return True
if self._lock:
with self._lock:
return _check_and_increment()
else:
return _check_and_increment()
def stop_rpm_counter(self):
if self._timer:
@@ -50,10 +56,18 @@ class RPMController(BaseModel):
self._current_rpm = 0
def _reset_request_count(self):
with self._lock:
def _reset():
self._current_rpm = 0
if not self._shutdown_flag:
self._timer = threading.Timer(60.0, self._reset_request_count)
self._timer.start()
if self._lock:
with self._lock:
_reset()
else:
_reset()
if self._timer:
self._shutdown_flag = True
self._timer.cancel()
self._timer = threading.Timer(60.0, self._reset_request_count)
self._timer.start()

View File

@@ -4,11 +4,6 @@ from unittest import mock
from unittest.mock import patch
import pytest
from langchain.tools import tool
from langchain_core.exceptions import OutputParserException
from langchain_openai import ChatOpenAI
from langchain.schema import AgentAction
from crewai import Agent, Crew, Task
from crewai.agents.cache import CacheHandler
from crewai.agents.executor import CrewAgentExecutor
@@ -16,6 +11,10 @@ from crewai.agents.parser import CrewAgentParser
from crewai.tools.tool_calling import InstructorToolCalling
from crewai.tools.tool_usage import ToolUsage
from crewai.utilities import RPMController
from langchain.schema import AgentAction
from langchain.tools import tool
from langchain_core.exceptions import OutputParserException
from langchain_openai import ChatOpenAI
def test_agent_creation():
@@ -817,7 +816,7 @@ def test_agent_definition_based_on_dict():
"verbose": True,
}
agent = Agent(config=config)
agent = Agent(**config)
assert agent.role == "test role"
assert agent.goal == "test goal"
@@ -837,7 +836,7 @@ def test_agent_human_input():
"backstory": "test backstory",
}
agent = Agent(config=config)
agent = Agent(**config)
task = Task(
agent=agent,

View File

@@ -8,7 +8,6 @@ from unittest.mock import MagicMock, patch
import pydantic_core
import pytest
from crewai.agent import Agent
from crewai.agents.cache import CacheHandler
from crewai.crew import Crew

View File

@@ -25,14 +25,20 @@ def mock_crew_factory():
MockCrewClass = type("MockCrew", (MagicMock, Crew), {})
class MockCrew(MockCrewClass):
def __deepcopy__(self, memo):
def __deepcopy__(self):
result = MockCrewClass()
result.kickoff_async = self.kickoff_async
result.name = self.name
return result
def copy(
self,
):
return self
crew = MockCrew()
crew.name = name
task_output = TaskOutput(
description="Test task", raw="Task output", agent="Test Agent"
)
@@ -44,9 +50,15 @@ def mock_crew_factory():
pydantic=pydantic_output,
)
async def async_kickoff(inputs=None):
async def kickoff_async(inputs=None):
return crew_output
# Create an AsyncMock for kickoff_async
crew.kickoff_async = AsyncMock(side_effect=kickoff_async)
# Mock the synchronous kickoff method
crew.kickoff = MagicMock(return_value=crew_output)
# Add more attributes that Procedure might be expecting
crew.verbose = False
crew.output_log_file = None
@@ -56,30 +68,16 @@ def mock_crew_factory():
crew.config = None
crew.cache = True
# # Create a valid Agent instance
mock_agent = Agent(
name="Mock Agent",
role="Mock Role",
goal="Mock Goal",
backstory="Mock Backstory",
allow_delegation=False,
verbose=False,
)
# Create a valid Task instance
mock_task = Task(
description="Return: Test output",
expected_output="Test output",
agent=mock_agent,
async_execution=False,
context=None,
)
# Add non-empty agents and tasks
mock_agent = MagicMock(spec=Agent)
mock_task = MagicMock(spec=Task)
mock_task.agent = mock_agent
mock_task.async_execution = False
mock_task.context = None
crew.agents = [mock_agent]
crew.tasks = [mock_task]
crew.kickoff_async = AsyncMock(side_effect=async_kickoff)
return crew
return _create_mock_crew
@@ -115,9 +113,7 @@ def mock_router_factory(mock_crew_factory):
(
"route1"
if x.get("score", 0) > 80
else "route2"
if x.get("score", 0) > 50
else "default"
else "route2" if x.get("score", 0) > 50 else "default"
),
)
)
@@ -477,31 +473,17 @@ async def test_pipeline_with_parallel_stages_end_in_single_stage(mock_crew_facto
"""
Test that Pipeline correctly handles parallel stages.
"""
crew1 = Crew(name="Crew 1", tasks=[task], agents=[agent])
crew2 = Crew(name="Crew 2", tasks=[task], agents=[agent])
crew3 = Crew(name="Crew 3", tasks=[task], agents=[agent])
crew4 = Crew(name="Crew 4", tasks=[task], agents=[agent])
crew1 = mock_crew_factory(name="Crew 1")
crew2 = mock_crew_factory(name="Crew 2")
crew3 = mock_crew_factory(name="Crew 3")
crew4 = mock_crew_factory(name="Crew 4")
pipeline = Pipeline(stages=[crew1, [crew2, crew3], crew4])
input_data = [{"initial": "data"}]
pipeline_result = await pipeline.kickoff(input_data)
with patch.object(Crew, "kickoff_async") as mock_kickoff:
mock_kickoff.return_value = CrewOutput(
raw="Test output",
tasks_output=[
TaskOutput(
description="Test task", raw="Task output", agent="Test Agent"
)
],
token_usage=DEFAULT_TOKEN_USAGE,
json_dict=None,
pydantic=None,
)
pipeline_result = await pipeline.kickoff(input_data)
mock_kickoff.assert_called_with(inputs={"initial": "data"})
crew1.kickoff_async.assert_called_once_with(inputs={"initial": "data"})
assert len(pipeline_result) == 1
pipeline_result_1 = pipeline_result[0]
@@ -649,33 +631,21 @@ Options:
@pytest.mark.asyncio
async def test_pipeline_data_accumulation():
crew1 = Crew(name="Crew 1", tasks=[task], agents=[agent])
crew2 = Crew(name="Crew 2", tasks=[task], agents=[agent])
async def test_pipeline_data_accumulation(mock_crew_factory):
crew1 = mock_crew_factory(name="Crew 1", output_json_dict={"key1": "value1"})
crew2 = mock_crew_factory(name="Crew 2", output_json_dict={"key2": "value2"})
pipeline = Pipeline(stages=[crew1, crew2])
input_data = [{"initial": "data"}]
results = await pipeline.kickoff(input_data)
with patch.object(Crew, "kickoff_async") as mock_kickoff:
mock_kickoff.side_effect = [
CrewOutput(
raw="Test output from Crew 1",
tasks_output=[],
token_usage=DEFAULT_TOKEN_USAGE,
json_dict={"key1": "value1"},
pydantic=None,
),
CrewOutput(
raw="Test output from Crew 2",
tasks_output=[],
token_usage=DEFAULT_TOKEN_USAGE,
json_dict={"key2": "value2"},
pydantic=None,
),
]
# Check that crew1 was called with only the initial input
crew1.kickoff_async.assert_called_once_with(inputs={"initial": "data"})
results = await pipeline.kickoff(input_data)
# Check that crew2 was called with the combined input from the initial data and crew1's output
crew2.kickoff_async.assert_called_once_with(
inputs={"initial": "data", "key1": "value1"}
)
# Check the final output
assert len(results) == 1

View File

@@ -14,6 +14,14 @@ class SimpleCrew:
def simple_task(self):
return Task(description="Simple Description", expected_output="Simple Output")
@task
def custom_named_task(self):
return Task(
description="Simple Description",
expected_output="Simple Output",
name="Custom",
)
def test_agent_memoization():
crew = SimpleCrew()
@@ -33,3 +41,15 @@ def test_task_memoization():
assert (
first_call_result is second_call_result
), "Task memoization is not working as expected"
def test_task_name():
simple_task = SimpleCrew().simple_task()
assert (
simple_task.name == "simple_task"
), "Task name is not inferred from function name as expected"
custom_named_task = SimpleCrew().custom_named_task()
assert (
custom_named_task.name == "Custom"
), "Custom task name is not being set as expected"

View File

@@ -1,8 +1,8 @@
"""Test Agent creation and execution basic functionality."""
import os
import hashlib
import json
import os
from unittest.mock import MagicMock, patch
import pytest
@@ -98,6 +98,7 @@ def test_task_callback():
task_completed = MagicMock(return_value="done")
task = Task(
name="Brainstorm",
description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
expected_output="Bullet point list of 5 interesting ideas.",
agent=researcher,
@@ -109,6 +110,10 @@ def test_task_callback():
task.execute_sync(agent=researcher)
task_completed.assert_called_once_with(task.output)
assert task.output.description == task.description
assert task.output.expected_output == task.expected_output
assert task.output.name == task.name
def test_task_callback_returns_task_output():
from crewai.tasks.output_format import OutputFormat
@@ -149,6 +154,8 @@ def test_task_callback_returns_task_output():
"json_dict": None,
"agent": researcher.role,
"summary": "Give me a list of 5 interesting ideas to explore...",
"name": None,
"expected_output": "Bullet point list of 5 interesting ideas.",
"output_format": OutputFormat.RAW,
}
assert output_dict == expected_output
@@ -696,7 +703,7 @@ def test_task_definition_based_on_dict():
"expected_output": "The score of the title.",
}
task = Task(config=config)
task = Task(**config)
assert task.description == config["description"]
assert task.expected_output == config["expected_output"]
@@ -709,7 +716,7 @@ def test_conditional_task_definition_based_on_dict():
"expected_output": "The score of the title.",
}
task = ConditionalTask(config=config, condition=lambda x: True)
task = ConditionalTask(**config, condition=lambda x: True)
assert task.description == config["description"]
assert task.expected_output == config["expected_output"]

View File

@@ -6,7 +6,11 @@ from langchain_openai import ChatOpenAI
from crewai.agent import Agent
from crewai.task import Task
from crewai.tasks.task_output import TaskOutput
from crewai.utilities.planning_handler import CrewPlanner, PlannerTaskPydanticOutput
from crewai.utilities.planning_handler import (
CrewPlanner,
PlannerTaskPydanticOutput,
PlanPerTask,
)
class TestCrewPlanner:
@@ -44,12 +48,17 @@ class TestCrewPlanner:
return CrewPlanner(tasks, planning_agent_llm)
def test_handle_crew_planning(self, crew_planner):
list_of_plans_per_task = [
PlanPerTask(task="Task1", plan="Plan 1"),
PlanPerTask(task="Task2", plan="Plan 2"),
PlanPerTask(task="Task3", plan="Plan 3"),
]
with patch.object(Task, "execute_sync") as execute:
execute.return_value = TaskOutput(
description="Description",
agent="agent",
pydantic=PlannerTaskPydanticOutput(
list_of_plans_per_task=["Plan 1", "Plan 2", "Plan 3"]
list_of_plans_per_task=list_of_plans_per_task
),
)
result = crew_planner._handle_crew_planning()
@@ -91,7 +100,9 @@ class TestCrewPlanner:
execute.return_value = TaskOutput(
description="Description",
agent="agent",
pydantic=PlannerTaskPydanticOutput(list_of_plans_per_task=["Plan 1"]),
pydantic=PlannerTaskPydanticOutput(
list_of_plans_per_task=[PlanPerTask(task="Task1", plan="Plan 1")]
),
)
result = crew_planner_different_llm._handle_crew_planning()