Compare commits

...

23 Commits

Author SHA1 Message Date
Brandon Hancock
a5f70d2307 fix unnecessary deps 2024-10-17 10:00:04 -04:00
Rip&Tear
b55fc40c83 Merge branch 'main' into feat/cli-model-selection-and-API-submission 2024-10-17 11:39:01 +08:00
Rip&Tear
d0ed4f5274 small comment cleanup 2024-10-17 11:25:37 +08:00
Rip&Tear
ee34399b71 refactor/Move functions into utils file, added new provider file and migrated fucntions thre, new constants file + general function refactor 2024-10-17 11:16:10 +08:00
Eduardo Chiarotti
798d16a6c6 feat: ADd warning from poetry -> uv (#1458) 2024-10-16 18:58:08 -03:00
Tony Kipkemboi
c9152f2af8 Upgrade docs to mirror change from Poetry to UV (#1451)
* Update docs to use  instead of

* Add Flows YouTube tutorial & link images
2024-10-16 10:57:41 -04:00
Stephen Hankinson
24b09e97cd use the same i18n as the agent for tool usage (#1440)
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2024-10-16 10:38:42 -04:00
Vini Brasil
a6b7295092 Adapt Tools CLI to uv (#1455)
* Adapt Tools CLI to UV

* Fix failing test
2024-10-16 10:55:04 -03:00
dbubel
725d159e44 fix typo in template file (#1432) 2024-10-14 16:51:04 -04:00
Stephen Hankinson
ef21da15e6 Correct the role for the message being added to the messages list (#1438)
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2024-10-14 16:49:16 -04:00
Muhammad Noman Fareed
de5d2eaa9b Fix Cache Typo in Documentation (#1441) 2024-10-14 16:30:31 -04:00
Stephen Hankinson
e2badaa4c6 Use a slice for the manager request. Make the task use the agent i18n settings (#1446) 2024-10-14 16:30:05 -04:00
Rip&Tear
39903f0c50 cleanup of comments 2024-10-13 18:14:09 +08:00
Rip&Tear
c4bf713113 refactored select_provider to have an ealry return 2024-10-13 18:13:24 +08:00
Rip&Tear
5d18c6312d refactered select_choice function for early return 2024-10-13 18:09:33 +08:00
Rip&Tear
1f9baf9b2c feat: implement crew creation CLI command
- refactor code to multiple functions
- Added ability for users to select provider and model when uing crewai create command and ave API key to .env
2024-10-13 00:04:05 +08:00
Rip&Tear
6fbc97b298 removed all unnecessary comments 2024-10-12 13:22:48 +08:00
Rip&Tear
08bacfa892 Merge branch 'feat/cli-model-selection-and-API-submission' of https://github.com/crewAIInc/crewAI into feat/cli-model-selection-and-API-submission 2024-10-12 13:06:16 +08:00
Rip&Tear
1ea8115d56 updated click prompt to remove default number 2024-10-12 13:05:55 +08:00
Eduardo Chiarotti
916dec2418 fix: training issue (#1433)
* fix: training issue

* fix: output from crew

* fix: message
2024-10-11 22:35:17 -03:00
Eduardo Chiarotti
7f387dd7c3 Feat/poetry to uv migration (#1406)
* feat: Start migrating to UV

* feat: add uv to flows

* feat: update docs on Poetry -> uv

* feat: update docs and uv.locl

* feat: update tests and github CI

* feat: run ruff format

* feat: update typechecking

* feat: fix type checking

* feat: update python version

* feat: type checking gic

* feat: adapt uv command to run the tool repo

* Adapt tool build command to uv

* feat: update logic to let only projects with crew to be deployed

* feat: add uv to tools

* fix; tests

* fix: remove breakpoint

* fix :test

* feat: add crewai update to migrate from poetry to uv

* fix: tests

* feat: add validation for ˆ character on pyproject

* feat: add run_crew to pyproject if doesnt exist

* feat: add validation for poetry migration

* fix: warning

---------

Co-authored-by: Vinicius Brasil <vini@hey.com>
2024-10-11 19:11:27 -03:00
Brandon Hancock (bhancock_ai)
6b906f09cf Merge branch 'main' into feat/cli-model-selection-and-API-submission 2024-10-11 14:44:24 -04:00
Rip&Tear
6c29ebafea updated CLI to allow for submitting API keys 2024-10-11 23:33:49 +08:00
52 changed files with 5909 additions and 654 deletions

View File

@@ -9,24 +9,24 @@ env:
OPENAI_API_KEY: fake-api-key
jobs:
deploy:
tests:
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Setup Python
uses: actions/setup-python@v4
- name: Install uv
uses: astral-sh/setup-uv@v3
with:
python-version: "3.11.9"
enable-cache: true
- name: Install Requirements
run: |
set -e
pip install poetry
poetry install
- name: Set up Python
run: uv python install 3.11.9
- name: Install the project
run: uv sync --dev
- name: Run tests
run: poetry run pytest
run: uv run pytest tests

View File

@@ -16,7 +16,7 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v4
with:
python-version: "3.10"
python-version: "3.11.9"
- name: Install Requirements
run: |

View File

@@ -44,15 +44,9 @@ To get started with CrewAI, follow these simple steps:
### 1. Installation
Ensure you have Python >=3.10 <=3.13 installed on your system. CrewAI uses [Poetry](https://python-poetry.org/) for dependency management and package handling, offering a seamless setup and execution experience.
Ensure you have Python >=3.10 <=3.13 installed on your system. CrewAI uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
First, if you haven't already, install Poetry:
```bash
pip install poetry
```
Then, install CrewAI:
First, install CrewAI:
```shell
pip install crewai
@@ -243,7 +237,7 @@ Lock the dependencies and install them by using the CLI command but first, navig
```shell
cd my_project
crewai install
crewai install (Optional)
```
To run your crew, execute the following command in the root of your project:
@@ -258,6 +252,12 @@ or
python src/my_project/main.py
```
If an error happens due to the usage of poetry, please run the following command to update your crewai package:
```bash
crewai update
```
You should see the output in the console and the `report.md` file should be created in the root of your project with the full final report.
In addition to the sequential process, you can use the hierarchical process, which automatically assigns a manager to the defined crew to properly coordinate the planning and execution of tasks through delegation and validation of results. [See more about the processes here](https://docs.crewai.com/core-concepts/Processes/).
@@ -332,14 +332,14 @@ CrewAI is open-source and we welcome contributions. If you're looking to contrib
### Installing Dependencies
```bash
poetry lock
poetry install
uv lock
uv sync
```
### Virtual Env
```bash
poetry shell
uv venv
```
### Pre-commit hooks
@@ -351,19 +351,19 @@ pre-commit install
### Running Tests
```bash
poetry run pytest
uvx pytest
```
### Running static type checks
```bash
poetry run mypy
uvx mypy
```
### Packaging
```bash
poetry build
uv build
```
### Installing Locally

View File

@@ -33,7 +33,7 @@ Think of an agent as a member of a team, with specific skills and a particular j
| **Verbose** *(optional)* | `verbose` | Setting this to `True` configures the internal logger to provide detailed execution logs, aiding in debugging and monitoring. Default is `False`. |
| **Allow Delegation** *(optional)* | `allow_delegation` | Agents can delegate tasks or questions to one another, ensuring that each task is handled by the most suitable agent. Default is `False`.
| **Step Callback** *(optional)* | `step_callback` | A function that is called after each step of the agent. This can be used to log the agent's actions or to perform other operations. It will overwrite the crew `step_callback`. |
| gbv vbn zzdsxcdsdfc**Cache** *(optional)* | `cache` | Indicates if the agent should use a cache for tool usage. Default is `True`. |
| **Cache** *(optional)* | `cache` | Indicates if the agent should use a cache for tool usage. Default is `True`. |
| **System Template** *(optional)* | `system_template` | Specifies the system format for the agent. Default is `None`. |
| **Prompt Template** *(optional)* | `prompt_template` | Specifies the prompt format for the agent. Default is `None`. |
| **Response Template** *(optional)* | `response_template` | Specifies the response format for the agent. Default is `None`. |

View File

@@ -10,10 +10,10 @@ The CrewAI CLI provides a set of commands to interact with CrewAI, allowing you
## Installation
To use the CrewAI CLI, make sure you have CrewAI & Poetry installed:
To use the CrewAI CLI, make sure you have CrewAI installed:
```shell
pip install crewai poetry
pip install crewai
```
## Basic Usage
@@ -145,4 +145,4 @@ crewai run
<Note>
Make sure to run these commands from the directory where your CrewAI project is set up.
Some commands may require additional configuration or setup within your project structure.
</Note>
</Note>

View File

@@ -572,16 +572,16 @@ In this example, the `PoemFlow` class defines a flow that generates a sentence c
### Running the Flow
Before running the flow, make sure to install the dependencies by running:
(Optional) Before running the flow, you can install the dependencies by running:
```bash
poetry install
crewai install
```
Once all of the dependencies are installed, you need to activate the virtual environment by running:
```bash
poetry shell
source .venv/bin/activate
```
After activating the virtual environment, you can run the flow by executing one of the following commands:
@@ -593,7 +593,7 @@ crewai flow run
or
```bash
poetry run run_flow
uv run run_flow
```
The flow will execute, and you should see the output in the console.
@@ -653,4 +653,17 @@ If you're interested in exploring additional examples of flows, we have a variet
4. **Meeting Assistant Flow**: This flow demonstrates how to broadcast one event to trigger multiple follow-up actions. For instance, after a meeting is completed, the flow can update a Trello board, send a Slack message, and save the results. It's a great example of handling multiple outcomes from a single event, making it ideal for comprehensive task management and notification systems. [View Example](https://github.com/crewAIInc/crewAI-examples/tree/main/meeting_assistant_flow)
By exploring these examples, you can gain insights into how to leverage CrewAI Flows for various use cases, from automating repetitive tasks to managing complex, multi-step processes with dynamic decision-making and human feedback.
By exploring these examples, you can gain insights into how to leverage CrewAI Flows for various use cases, from automating repetitive tasks to managing complex, multi-step processes with dynamic decision-making and human feedback.
Also, check out our YouTube video on how to use flows in CrewAI below!
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/MTb5my6VOT8"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
allowfullscreen
></iframe>

View File

@@ -1,277 +0,0 @@
---
title: Pipelines
description: Understanding and utilizing pipelines in the crewAI framework for efficient multi-stage task processing.
icon: timeline-arrow
---
## What is a Pipeline?
A pipeline in CrewAI represents a structured workflow that allows for the sequential or parallel execution of multiple crews. It provides a way to organize complex processes involving multiple stages, where the output of one stage can serve as input for subsequent stages.
## Key Terminology
Understanding the following terms is crucial for working effectively with pipelines:
- **Stage**: A distinct part of the pipeline, which can be either sequential (a single crew) or parallel (multiple crews executing concurrently).
- **Kickoff**: A specific execution of the pipeline for a given set of inputs, representing a single instance of processing through the pipeline.
- **Branch**: Parallel executions within a stage (e.g., concurrent crew operations).
- **Trace**: The journey of an individual input through the entire pipeline, capturing the path and transformations it undergoes.
Example pipeline structure:
```bash Pipeline
crew1 >> [crew2, crew3] >> crew4
```
This represents a pipeline with three stages:
1. A sequential stage (crew1)
2. A parallel stage with two branches (crew2 and crew3 executing concurrently)
3. Another sequential stage (crew4)
Each input creates its own kickoff, flowing through all stages of the pipeline. Multiple kickoffs can be processed concurrently, each following the defined pipeline structure.
## Pipeline Attributes
| Attribute | Parameters | Description |
| :--------- | :---------- | :----------------------------------------------------------------------------------------------------------------- |
| **Stages** | `stages` | A list of `PipelineStage` (crews, lists of crews, or routers) representing the stages to be executed in sequence. |
## Creating a Pipeline
When creating a pipeline, you define a series of stages, each consisting of either a single crew or a list of crews for parallel execution.
The pipeline ensures that each stage is executed in order, with the output of one stage feeding into the next.
### Example: Assembling a Pipeline
```python
from crewai import Crew, Process, Pipeline
# Define your crews
research_crew = Crew(
agents=[researcher],
tasks=[research_task],
process=Process.sequential
)
analysis_crew = Crew(
agents=[analyst],
tasks=[analysis_task],
process=Process.sequential
)
writing_crew = Crew(
agents=[writer],
tasks=[writing_task],
process=Process.sequential
)
# Assemble the pipeline
my_pipeline = Pipeline(
stages=[research_crew, analysis_crew, writing_crew]
)
```
## Pipeline Methods
| Method | Description |
| :--------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **kickoff** | Executes the pipeline, processing all stages and returning the results. This method initiates one or more kickoffs through the pipeline, handling the flow of data between stages. |
| **process_runs** | Runs the pipeline for each input provided, handling the flow and transformation of data between stages. |
## Pipeline Output
The output of a pipeline in the CrewAI framework is encapsulated within the `PipelineKickoffResult` class.
This class provides a structured way to access the results of the pipeline's execution, including various formats such as raw strings, JSON, and Pydantic models.
### Pipeline Output Attributes
| Attribute | Parameters | Type | Description |
| :-------------- | :------------ | :------------------------ | :-------------------------------------------------------------------------------------------------------- |
| **ID** | `id` | `UUID4` | A unique identifier for the pipeline output. |
| **Run Results** | `run_results` | `List[PipelineRunResult]` | A list of `PipelineRunResult` objects, each representing the output of a single run through the pipeline. |
### Pipeline Output Methods
| Method/Property | Description |
| :----------------- | :----------------------------------------------------- |
| **add_run_result** | Adds a `PipelineRunResult` to the list of run results. |
### Pipeline Run Result Attributes
| Attribute | Parameters | Type | Description |
| :---------------- | :-------------- | :------------------------- | :-------------------------------------------------------------------------------------------- |
| **ID** | `id` | `UUID4` | A unique identifier for the run result. |
| **Raw** | `raw` | `str` | The raw output of the final stage in the pipeline kickoff. |
| **Pydantic** | `pydantic` | `Any` | A Pydantic model object representing the structured output of the final stage, if applicable. |
| **JSON Dict** | `json_dict` | `Union[Dict[str, Any], None]` | A dictionary representing the JSON output of the final stage, if applicable. |
| **Token Usage** | `token_usage` | `Dict[str, UsageMetrics]` | A summary of token usage across all stages of the pipeline kickoff. |
| **Trace** | `trace` | `List[Any]` | A trace of the journey of inputs through the pipeline kickoff. |
| **Crews Outputs** | `crews_outputs` | `List[CrewOutput]` | A list of `CrewOutput` objects, representing the outputs from each crew in the pipeline kickoff. |
### Pipeline Run Result Methods and Properties
| Method/Property | Description |
| :-------------- | :------------------------------------------------------------------------------------------------------- |
| **json** | Returns the JSON string representation of the run result if the output format of the final task is JSON. |
| **to_dict** | Converts the JSON and Pydantic outputs to a dictionary. |
| **str** | Returns the string representation of the run result, prioritizing Pydantic, then JSON, then raw. |
### Accessing Pipeline Outputs
Once a pipeline has been executed, its output can be accessed through the `PipelineOutput` object returned by the `process_runs` method.
The `PipelineOutput` class provides access to individual `PipelineRunResult` objects, each representing a single run through the pipeline.
#### Example
```python
# Define input data for the pipeline
input_data = [
{"initial_query": "Latest advancements in AI"},
{"initial_query": "Future of robotics"}
]
# Execute the pipeline
pipeline_output = await my_pipeline.process_runs(input_data)
# Access the results
for run_result in pipeline_output.run_results:
print(f"Run ID: {run_result.id}")
print(f"Final Raw Output: {run_result.raw}")
if run_result.json_dict:
print(f"JSON Output: {json.dumps(run_result.json_dict, indent=2)}")
if run_result.pydantic:
print(f"Pydantic Output: {run_result.pydantic}")
print(f"Token Usage: {run_result.token_usage}")
print(f"Trace: {run_result.trace}")
print("Crew Outputs:")
for crew_output in run_result.crews_outputs:
print(f" Crew: {crew_output.raw}")
print("\n")
```
This example demonstrates how to access and work with the pipeline output, including individual run results and their associated data.
## Using Pipelines
Pipelines are particularly useful for complex workflows that involve multiple stages of processing, analysis, or content generation. They allow you to:
1. **Sequence Operations**: Execute crews in a specific order, ensuring that the output of one crew is available as input to the next.
2. **Parallel Processing**: Run multiple crews concurrently within a stage for increased efficiency.
3. **Manage Complex Workflows**: Break down large tasks into smaller, manageable steps executed by specialized crews.
### Example: Running a Pipeline
```python
# Define input data for the pipeline
input_data = [{"initial_query": "Latest advancements in AI"}]
# Execute the pipeline, initiating a run for each input
results = await my_pipeline.process_runs(input_data)
# Access the results
for result in results:
print(f"Final Output: {result.raw}")
print(f"Token Usage: {result.token_usage}")
print(f"Trace: {result.trace}") # Shows the path of the input through all stages
```
## Advanced Features
### Parallel Execution within Stages
You can define parallel execution within a stage by providing a list of crews, creating multiple branches:
```python
parallel_analysis_crew = Crew(agents=[financial_analyst], tasks=[financial_analysis_task])
market_analysis_crew = Crew(agents=[market_analyst], tasks=[market_analysis_task])
my_pipeline = Pipeline(
stages=[
research_crew,
[parallel_analysis_crew, market_analysis_crew], # Parallel execution (branching)
writing_crew
]
)
```
### Routers in Pipelines
Routers are a powerful feature in crewAI pipelines that allow for dynamic decision-making and branching within your workflow.
They enable you to direct the flow of execution based on specific conditions or criteria, making your pipelines more flexible and adaptive.
#### What is a Router?
A router in crewAI is a special component that can be included as a stage in your pipeline. It evaluates the input data and determines which path the execution should take next.
This allows for conditional branching in your pipeline, where different crews or sub-pipelines can be executed based on the router's decision.
#### Key Components of a Router
1. **Routes**: A dictionary of named routes, each associated with a condition and a pipeline to execute if the condition is met.
2. **Default Route**: A fallback pipeline that is executed if none of the defined route conditions are met.
#### Creating a Router
Here's an example of how to create a router:
```python
from crewai import Router, Route, Pipeline, Crew, Agent, Task
# Define your agents
classifier = Agent(name="Classifier", role="Email Classifier")
urgent_handler = Agent(name="Urgent Handler", role="Urgent Email Processor")
normal_handler = Agent(name="Normal Handler", role="Normal Email Processor")
# Define your tasks
classify_task = Task(description="Classify the email based on its content and metadata.")
urgent_task = Task(description="Process and respond to urgent email quickly.")
normal_task = Task(description="Process and respond to normal email thoroughly.")
# Define your crews
classification_crew = Crew(agents=[classifier], tasks=[classify_task]) # classify email between high and low urgency 1-10
urgent_crew = Crew(agents=[urgent_handler], tasks=[urgent_task])
normal_crew = Crew(agents=[normal_handler], tasks=[normal_task])
# Create pipelines for different urgency levels
urgent_pipeline = Pipeline(stages=[urgent_crew])
normal_pipeline = Pipeline(stages=[normal_crew])
# Create a router
email_router = Router(
routes={
"high_urgency": Route(
condition=lambda x: x.get("urgency_score", 0) > 7,
pipeline=urgent_pipeline
),
"low_urgency": Route(
condition=lambda x: x.get("urgency_score", 0) <= 7,
pipeline=normal_pipeline
)
},
default=Pipeline(stages=[normal_pipeline]) # Default to just normal if no urgency score
)
# Use the router in a main pipeline
main_pipeline = Pipeline(stages=[classification_crew, email_router])
inputs = [{"email": "..."}, {"email": "..."}] # List of email data
main_pipeline.kickoff(inputs=inputs)
```
In this example, the router decides between an urgent pipeline and a normal pipeline based on the urgency score of the email. If the urgency score is greater than 7,
it routes to the urgent pipeline; otherwise, it uses the normal pipeline. If the input doesn't include an urgency score, it defaults to just the classification crew.
#### Benefits of Using Routers
1. **Dynamic Workflow**: Adapt your pipeline's behavior based on input characteristics or intermediate results.
2. **Efficiency**: Route urgent tasks to quicker processes, reserving more thorough pipelines for less time-sensitive inputs.
3. **Flexibility**: Easily modify or extend your pipeline's logic without changing the core structure.
4. **Scalability**: Handle a wide range of email types and urgency levels with a single pipeline structure.
### Error Handling and Validation
The `Pipeline` class includes validation mechanisms to ensure the robustness of the pipeline structure:
- Validates that stages contain only Crew instances or lists of Crew instances.
- Prevents double nesting of stages to maintain a clear structure.

View File

@@ -25,9 +25,9 @@ It provides a dashboard for tracking agent performance, session replays, and cus
Additionally, AgentOps provides session drilldowns for viewing Crew agent interactions, LLM calls, and tool usage in real-time.
This feature is useful for debugging and understanding how agents interact with users as well as other agents.
![Overview of a select series of agent session runs](images/agentops-overview.png)
![Overview of session drilldowns for examining agent runs](images/agentops-session.png)
![Viewing a step-by-step agent replay execution graph](images/agentops-replay.png)
![Overview of a select series of agent session runs](/images/agentops-overview.png)
![Overview of session drilldowns for examining agent runs](/images/agentops-session.png)
![Viewing a step-by-step agent replay execution graph](/images/agentops-replay.png)
### Features
@@ -123,4 +123,4 @@ For feature requests or bug reports, please reach out to the AgentOps team on th
<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
<a href="https://app.agentops.ai/?=crew">🖇️ AgentOps Dashboard</a>
<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
<a href="https://docs.agentops.ai/introduction">📙 Documentation</a>
<a href="https://docs.agentops.ai/introduction">📙 Documentation</a>

View File

@@ -10,9 +10,9 @@ Langtrace is an open-source, external tool that helps you set up observability a
While not built directly into CrewAI, Langtrace can be used alongside CrewAI to gain deep visibility into the cost, latency, and performance of your CrewAI Agents.
This integration allows you to log hyperparameters, monitor performance regressions, and establish a process for continuous improvement of your Agents.
![Overview of a select series of agent session runs](images/langtrace1.png)
![Overview of agent traces](images/langtrace2.png)
![Overview of llm traces in details](images/langtrace3.png)
![Overview of a select series of agent session runs](/images/langtrace1.png)
![Overview of agent traces](/images/langtrace2.png)
![Overview of llm traces in details](/images/langtrace3.png)
## Setup Instructions
@@ -69,4 +69,4 @@ This integration allows you to log hyperparameters, monitor performance regressi
6. **Testing and Evaluations**
- Set up automated tests for your CrewAI agents and tasks.
- Set up automated tests for your CrewAI agents and tasks.

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@@ -1,11 +1,9 @@
---
title: Installation & Setup
title: Installation
description:
icon: wrench
---
## Install CrewAI
This guide will walk you through the installation process for CrewAI and its dependencies.
CrewAI is a flexible and powerful AI framework that enables you to create and manage AI agents, tools, and tasks efficiently.
Let's get started! 🚀
@@ -15,17 +13,8 @@ Let's get started! 🚀
</Tip>
<Steps>
<Step title="Install Poetry">
First, if you haven't already, install [Poetry](https://python-poetry.org/).
CrewAI uses Poetry for dependency management and package handling, offering a seamless setup and execution experience.
<CodeGroup>
```shell Terminal
pip install poetry
```
</CodeGroup>
</Step>
<Step title="Install CrewAI">
Then, install the main CrewAI package:
Install the main CrewAI package with the following command:
<CodeGroup>
```shell Terminal
pip install crewai
@@ -45,15 +34,29 @@ Let's get started! 🚀
</CodeGroup>
</Step>
<Step title="Upgrade CrewAI">
To upgrade CrewAI and CrewAI Tools to the latest version, run the following command:
To upgrade CrewAI and CrewAI Tools to the latest version, run the following command
<CodeGroup>
```shell Terminal
pip install --upgrade crewai crewai-tools
```
</CodeGroup>
<Note>
1. If you're using an older version of CrewAI, you may receive a warning about using `Poetry` for dependency management.
![Error from older versions](./images/crewai-run-poetry-error.png)
2. In this case, you'll need to run the command below to update your project.
This command will migrate your project to use [UV](https://github.com/astral-sh/uv) and update the necessary files.
```shell Terminal
crewai update
```
3. After running the command above, you should see the following output:
![Successfully migrated to UV](./images/crewai-update.png)
4. You're all set! You can now proceed to the next step! 🎉
</Note>
</Step>
<Step title="Verify the installation">
To verify that `crewai` and `crewai-tools` are installed correctly, run the following command:
To verify that `crewai` and `crewai-tools` are installed correctly, run the following command
<CodeGroup>
```shell Terminal
pip freeze | grep crewai

View File

@@ -45,5 +45,5 @@ By fostering collaborative intelligence, CrewAI empowers agents to work together
## Next Step
- [Install CrewAI](/installation)
- [Install CrewAI](/installation) to get started with your first agent.

View File

@@ -66,18 +66,17 @@
"pages": [
"concepts/agents",
"concepts/tasks",
"concepts/tools",
"concepts/processes",
"concepts/crews",
"concepts/flows",
"concepts/llms",
"concepts/processes",
"concepts/collaboration",
"concepts/pipeline",
"concepts/training",
"concepts/memory",
"concepts/planning",
"concepts/testing",
"concepts/flows",
"concepts/cli",
"concepts/llms",
"concepts/tools",
"concepts/langchain-tools",
"concepts/llamaindex-tools"
]

View File

@@ -26,6 +26,7 @@ Follow the steps below to get crewing! 🚣‍♂️
<Step title="Modify your `agents.yaml` file">
<Tip>
You can also modify the agents as needed to fit your use case or copy and paste as is to your project.
Any variable interpolated in your `agents.yaml` and `tasks.yaml` files like `{topic}` will be replaced by the value of the variable in the `main.py` file.
</Tip>
```yaml agents.yaml
# src/latest_ai_development/config/agents.yaml
@@ -124,7 +125,7 @@ Follow the steps below to get crewing! 🚣‍♂️
```
</Step>
<Step title="Feel free to pass custom inputs to your crew">
For example, you can pass the `topic` input to your crew to customize the research and reporting to medical llms or any other topic.
For example, you can pass the `topic` input to your crew to customize the research and reporting.
```python main.py
#!/usr/bin/env python
# src/latest_ai_development/main.py
@@ -233,6 +234,74 @@ Follow the steps below to get crewing! 🚣‍♂️
</Step>
</Steps>
### Note on Consistency in Naming
The names you use in your YAML files (`agents.yaml` and `tasks.yaml`) should match the method names in your Python code.
For example, you can reference the agent for specific tasks from `tasks.yaml` file.
This naming consistency allows CrewAI to automatically link your configurations with your code; otherwise, your task won't recognize the reference properly.
#### Example References
<Tip>
Note how we use the same name for the agent in the `agents.yaml` (`email_summarizer`) file as the method name in the `crew.py` (`email_summarizer`) file.
</Tip>
```yaml agents.yaml
email_summarizer:
role: >
Email Summarizer
goal: >
Summarize emails into a concise and clear summary
backstory: >
You will create a 5 bullet point summary of the report
llm: mixtal_llm
```
<Tip>
Note how we use the same name for the agent in the `tasks.yaml` (`email_summarizer_task`) file as the method name in the `crew.py` (`email_summarizer_task`) file.
</Tip>
```yaml tasks.yaml
email_summarizer_task:
description: >
Summarize the email into a 5 bullet point summary
expected_output: >
A 5 bullet point summary of the email
agent: email_summarizer
context:
- reporting_task
- research_task
```
Use the annotations to properly reference the agent and task in the `crew.py` file.
### Annotations include:
* `@agent`
* `@task`
* `@crew`
* `@tool`
* `@callback`
* `@output_json`
* `@output_pydantic`
* `@cache_handler`
```python crew.py
# ...
@agent
def email_summarizer(self) -> Agent:
return Agent(
config=self.agents_config["email_summarizer"],
)
@task
def email_summarizer_task(self) -> Task:
return Task(
config=self.tasks_config["email_summarizer_task"],
)
# ...
```
<Tip>
In addition to the [sequential process](../how-to/sequential-process), you can use the [hierarchical process](../how-to/hierarchical-process),
which automatically assigns a manager to the defined crew to properly coordinate the planning and execution of tasks through delegation and validation of results.
@@ -241,7 +310,7 @@ You can learn more about the core concepts [here](/concepts).
### Replay Tasks from Latest Crew Kickoff
CrewAI now includes a replay feature that allows you to list the tasks from the last run and replay from a specific one. To use this feature, run:
CrewAI now includes a replay feature that allows you to list the tasks from the last run and replay from a specific one. To use this feature, run.
```shell
crewai replay <task_id>

View File

@@ -1,65 +1,66 @@
[tool.poetry]
[project]
name = "crewai"
version = "0.70.1"
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"
packages = [{ include = "crewai", from = "src" }]
requires-python = ">=3.10,<=3.13"
authors = [
{ name = "Joao Moura", email = "joao@crewai.com" }
]
dependencies = [
"pydantic>=2.4.2",
"langchain>=0.2.16",
"openai>=1.13.3",
"opentelemetry-api>=1.22.0",
"opentelemetry-sdk>=1.22.0",
"opentelemetry-exporter-otlp-proto-http>=1.22.0",
"instructor>=1.3.3",
"regex>=2024.9.11",
"crewai-tools>=0.12.1",
"click>=8.1.7",
"python-dotenv>=1.0.0",
"appdirs>=1.4.4",
"jsonref>=1.1.0",
"agentops>=0.3.0",
"embedchain>=0.1.114",
"json-repair>=0.25.2",
"auth0-python>=4.7.1",
"litellm>=1.44.22",
"pyvis>=0.3.2",
"uv>=0.4.18",
"tomli-w>=1.1.0",
]
[tool.poetry.urls]
[project.urls]
Homepage = "https://crewai.com"
Documentation = "https://docs.crewai.com"
Repository = "https://github.com/crewAIInc/crewAI"
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
pydantic = "^2.4.2"
langchain = "^0.2.16"
openai = "^1.13.3"
opentelemetry-api = "^1.22.0"
opentelemetry-sdk = "^1.22.0"
opentelemetry-exporter-otlp-proto-http = "^1.22.0"
instructor = "1.3.3"
regex = "^2024.9.11"
crewai-tools = { version = "^0.12.1", optional = true }
click = "^8.1.7"
python-dotenv = "^1.0.0"
appdirs = "^1.4.4"
jsonref = "^1.1.0"
agentops = { version = "^0.3.0", optional = true }
embedchain = "^0.1.114"
json-repair = "^0.25.2"
auth0-python = "^4.7.1"
poetry = "^1.8.3"
litellm = "^1.44.22"
pyvis = "^0.3.2"
[project.optional-dependencies]
tools = ["crewai-tools>=0.12.1"]
agentops = ["agentops>=0.3.0"]
[tool.poetry.extras]
tools = ["crewai-tools"]
agentops = ["agentops"]
[tool.uv]
dev-dependencies = [
"ruff>=0.4.10",
"mypy>=1.10.0",
"pre-commit>=3.6.0",
"mkdocs>=1.4.3",
"mkdocstrings>=0.22.0",
"mkdocstrings-python>=1.1.2",
"mkdocs-material>=9.5.7",
"mkdocs-material-extensions>=1.3.1",
"pillow>=10.2.0",
"cairosvg>=2.7.1",
"crewai-tools>=0.12.1",
"pytest>=8.0.0",
"pytest-vcr>=1.0.2",
"python-dotenv>=1.0.0",
"pytest-asyncio>=0.23.7",
"pytest-subprocess>=1.5.2",
]
[tool.poetry.group.dev.dependencies]
isort = "^5.13.2"
mypy = "1.10.0"
autoflake = "^2.2.1"
pre-commit = "^3.6.0"
mkdocs = "^1.4.3"
mkdocstrings = "^0.22.0"
mkdocstrings-python = "^1.1.2"
mkdocs-material = { extras = ["imaging"], version = "^9.5.7" }
mkdocs-material-extensions = "^1.3.1"
pillow = "^10.2.0"
cairosvg = "^2.7.1"
crewai-tools = "^0.12.1"
[tool.poetry.group.test.dependencies]
pytest = "^8.0.0"
pytest-vcr = "^1.0.2"
python-dotenv = "1.0.0"
pytest-asyncio = "^0.23.7"
pytest-subprocess = "^1.5.2"
[tool.poetry.scripts]
[project.scripts]
crewai = "crewai.cli.cli:crewai"
[tool.mypy]
@@ -71,5 +72,5 @@ exclude = ["cli/templates"]
exclude_dirs = ["src/crewai/cli/templates"]
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
requires = ["hatchling"]
build-backend = "hatchling.build"

View File

@@ -81,6 +81,7 @@ class BaseAgentTools(BaseModel, ABC):
task_with_assigned_agent = Task( # type: ignore # Incompatible types in assignment (expression has type "Task", variable has type "str")
description=task,
agent=agent,
expected_output="Your best answer to your coworker asking you this, accounting for the context shared.",
expected_output=agent.i18n.slice("manager_request"),
i18n=agent.i18n,
)
return agent.execute_task(task_with_assigned_agent, context)

View File

@@ -151,7 +151,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
)
self.have_forced_answer = True
self.messages.append(
self._format_msg(formatted_answer.text, role="user")
self._format_msg(formatted_answer.text, role="assistant")
)
except OutputParserException as e:
@@ -317,9 +317,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
if self.crew is not None and hasattr(self.crew, "_train_iteration"):
train_iteration = self.crew._train_iteration
if agent_id in training_data and isinstance(train_iteration, int):
training_data[agent_id][train_iteration][
"improved_output"
] = result.output
training_data[agent_id][train_iteration]["improved_output"] = (
result.output
)
training_handler.save(training_data)
else:
self._logger.log(
@@ -334,6 +334,32 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
color="red",
)
if self.ask_for_human_input and human_feedback is not None:
training_data = {
"initial_output": result.output,
"human_feedback": human_feedback,
"agent": agent_id,
"agent_role": self.agent.role,
}
if self.crew is not None and hasattr(self.crew, "_train_iteration"):
train_iteration = self.crew._train_iteration
if isinstance(train_iteration, int):
CrewTrainingHandler(TRAINING_DATA_FILE).append(
train_iteration, agent_id, training_data
)
else:
self._logger.log(
"error",
"Invalid train iteration type. Expected int.",
color="red",
)
else:
self._logger.log(
"error",
"Crew is None or does not have _train_iteration attribute.",
color="red",
)
def _format_prompt(self, prompt: str, inputs: Dict[str, str]) -> str:
prompt = prompt.replace("{input}", inputs["input"])
prompt = prompt.replace("{tool_names}", inputs["tool_names"])

View File

@@ -21,6 +21,7 @@ from .run_crew import run_crew
from .run_flow import run_flow
from .tools.main import ToolCommand
from .train_crew import train_crew
from .update_crew import update_crew
@click.group()
@@ -188,6 +189,12 @@ def run():
run_crew()
@crewai.command()
def update():
"""Update the pyproject.toml of the Crew project to use uv."""
update_crew()
@crewai.command()
def signup():
"""Sign Up/Login to CrewAI+."""
@@ -276,7 +283,13 @@ def tool_install(handle: str):
@tool.command(name="publish")
@click.option("--force", is_flag=True, show_default=True, default=False, help="Bypasses Git remote validations")
@click.option(
"--force",
is_flag=True,
show_default=True,
default=False,
help="Bypasses Git remote validations",
)
@click.option("--public", "is_public", flag_value=True, default=False)
@click.option("--private", "is_public", flag_value=False)
def tool_publish(is_public: bool, force: bool):

View File

@@ -0,0 +1,19 @@
ENV_VARS = {
'openai': ['OPENAI_API_KEY'],
'anthropic': ['ANTHROPIC_API_KEY'],
'gemini': ['GEMINI_API_KEY'],
'groq': ['GROQ_API_KEY'],
'ollama': ['FAKE_KEY'],
}
PROVIDERS = ['openai', 'anthropic', 'gemini', 'groq', 'ollama']
MODELS = {
'openai': ['gpt-4', 'gpt-4o', 'gpt-4o-mini', 'o1-mini', 'o1-preview'],
'anthropic': ['claude-3-5-sonnet-20240620', 'claude-3-sonnet-20240229', 'claude-3-opus-20240229', 'claude-3-haiku-20240307'],
'gemini': ['gemini-1.5-flash', 'gemini-1.5-pro', 'gemini-gemma-2-9b-it', 'gemini-gemma-2-27b-it'],
'groq': ['llama-3.1-8b-instant', 'llama-3.1-70b-versatile', 'llama-3.1-405b-reasoning', 'gemma2-9b-it', 'gemma-7b-it'],
'ollama': ['llama3.1', 'mixtral'],
}
JSON_URL = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"

View File

@@ -1,12 +1,10 @@
from pathlib import Path
import click
from crewai.cli.utils import copy_template,load_env_vars, write_env_file
from crewai.cli.provider import get_provider_data, select_provider, select_model, PROVIDERS
from crewai.cli.constants import ENV_VARS
from crewai.cli.utils import copy_template
def create_crew(name, parent_folder=None):
"""Create a new crew."""
def create_folder_structure(name, parent_folder=None):
folder_name = name.replace(" ", "_").replace("-", "_").lower()
class_name = name.replace("_", " ").replace("-", " ").title().replace(" ", "")
@@ -28,19 +26,83 @@ def create_crew(name, parent_folder=None):
(folder_path / "src" / folder_name).mkdir(parents=True)
(folder_path / "src" / folder_name / "tools").mkdir(parents=True)
(folder_path / "src" / folder_name / "config").mkdir(parents=True)
with open(folder_path / ".env", "w") as file:
file.write("OPENAI_API_KEY=YOUR_API_KEY")
else:
click.secho(
f"\tFolder {folder_name} already exists. Please choose a different name.",
fg="red",
f"\tFolder {folder_name} already exists.",
fg="yellow",
)
return folder_path, folder_name, class_name
def copy_template_files(folder_path, name, class_name, parent_folder):
package_dir = Path(__file__).parent
templates_dir = package_dir / "templates" / "crew"
root_template_files = (
[".gitignore", "pyproject.toml", "README.md"] if not parent_folder else []
)
tools_template_files = ["tools/custom_tool.py", "tools/__init__.py"]
config_template_files = ["config/agents.yaml", "config/tasks.yaml"]
src_template_files = (
["__init__.py", "main.py", "crew.py"] if not parent_folder else ["crew.py"]
)
for file_name in root_template_files:
src_file = templates_dir / file_name
dst_file = folder_path / file_name
copy_template(src_file, dst_file, name, class_name, folder_path.name)
src_folder = folder_path / "src" / folder_path.name if not parent_folder else folder_path
for file_name in src_template_files:
src_file = templates_dir / file_name
dst_file = src_folder / file_name
copy_template(src_file, dst_file, name, class_name, folder_path.name)
if not parent_folder:
for file_name in tools_template_files + config_template_files:
src_file = templates_dir / file_name
dst_file = src_folder / file_name
copy_template(src_file, dst_file, name, class_name, folder_path.name)
def create_crew(name, parent_folder=None):
folder_path, folder_name, class_name = create_folder_structure(name, parent_folder)
env_vars = load_env_vars(folder_path)
provider_models = get_provider_data()
if not provider_models:
return
selected_provider = select_provider(provider_models)
if not selected_provider:
return
provider = selected_provider
selected_model = select_model(provider, provider_models)
if not selected_model:
return
model = selected_model
if provider in PROVIDERS:
api_key_var = ENV_VARS[provider][0]
else:
api_key_var = click.prompt(
f"Enter the environment variable name for your {provider.capitalize()} API key",
type=str
)
env_vars = {api_key_var: "YOUR_API_KEY_HERE"}
write_env_file(folder_path, env_vars)
env_vars['MODEL'] = model
click.secho(f"Selected model: {model}", fg="green")
package_dir = Path(__file__).parent
templates_dir = package_dir / "templates" / "crew"
# List of template files to copy
root_template_files = (
[".gitignore", "pyproject.toml", "README.md"] if not parent_folder else []
)

View File

@@ -5,13 +5,13 @@ import click
def evaluate_crew(n_iterations: int, model: str) -> None:
"""
Test and Evaluate the crew by running a command in the Poetry environment.
Test and Evaluate the crew by running a command in the UV environment.
Args:
n_iterations (int): The number of iterations to test the crew.
model (str): The model to test the crew with.
"""
command = ["poetry", "run", "test", str(n_iterations), model]
command = ["uv", "run", "test", str(n_iterations), model]
try:
if n_iterations <= 0:

View File

@@ -5,13 +5,10 @@ import click
def install_crew() -> None:
"""
Install the crew by running the Poetry command to lock and install.
Install the crew by running the UV 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
)
subprocess.run(["uv", "sync"], 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)

View File

@@ -5,9 +5,9 @@ import click
def plot_flow() -> None:
"""
Plot the flow by running a command in the Poetry environment.
Plot the flow by running a command in the UV environment.
"""
command = ["poetry", "run", "plot_flow"]
command = ["uv", "run", "plot_flow"]
try:
result = subprocess.run(command, capture_output=False, text=True, check=True)

View File

@@ -25,7 +25,9 @@ class PlusAPI:
def _make_request(self, method: str, endpoint: str, **kwargs) -> requests.Response:
url = urljoin(self.base_url, endpoint)
return requests.request(method, url, headers=self.headers, **kwargs)
session = requests.Session()
session.trust_env = False
return session.request(method, url, headers=self.headers, **kwargs)
def login_to_tool_repository(self):
return self._make_request("POST", f"{self.TOOLS_RESOURCE}/login")

186
src/crewai/cli/provider.py Normal file
View File

@@ -0,0 +1,186 @@
import json
import time
import requests
from collections import defaultdict
import click
from pathlib import Path
from crewai.cli.constants import PROVIDERS, MODELS, JSON_URL
def select_choice(prompt_message, choices):
"""
Presents a list of choices to the user and prompts them to select one.
Args:
- prompt_message (str): The message to display to the user before presenting the choices.
- choices (list): A list of options to present to the user.
Returns:
- str: The selected choice from the list, or None if the operation is aborted or an invalid selection is made.
"""
click.secho(prompt_message, fg="cyan")
for idx, choice in enumerate(choices, start=1):
click.secho(f"{idx}. {choice}", fg="cyan")
try:
selected_index = click.prompt("Enter the number of your choice", type=int) - 1
except click.exceptions.Abort:
click.secho("Operation aborted by the user.", fg="red")
return None
if not (0 <= selected_index < len(choices)):
click.secho("Invalid selection.", fg="red")
return None
return choices[selected_index]
def select_provider(provider_models):
"""
Presents a list of providers to the user and prompts them to select one.
Args:
- provider_models (dict): A dictionary of provider models.
Returns:
- str: The selected provider, or None if the operation is aborted or an invalid selection is made.
"""
predefined_providers = [p.lower() for p in PROVIDERS]
all_providers = sorted(set(predefined_providers + list(provider_models.keys())))
provider = select_choice("Select a provider to set up:", predefined_providers + ['other'])
if not provider:
return None
provider = provider.lower()
if provider == 'other':
provider = select_choice("Select a provider from the full list:", all_providers)
if not provider:
return None
return provider
def select_model(provider, provider_models):
"""
Presents a list of models for a given provider to the user and prompts them to select one.
Args:
- provider (str): The provider for which to select a model.
- provider_models (dict): A dictionary of provider models.
Returns:
- str: The selected model, or None if the operation is aborted or an invalid selection is made.
"""
predefined_providers = [p.lower() for p in PROVIDERS]
if provider in predefined_providers:
available_models = MODELS.get(provider, [])
else:
available_models = provider_models.get(provider, [])
if not available_models:
click.secho(f"No models available for provider '{provider}'.", fg="red")
return None
selected_model = select_choice(f"Select a model to use for {provider.capitalize()}:", available_models)
return selected_model
def load_provider_data(cache_file, cache_expiry):
"""
Loads provider data from a cache file if it exists and is not expired. If the cache is expired or corrupted, it fetches the data from the web.
Args:
- cache_file (Path): The path to the cache file.
- cache_expiry (int): The cache expiry time in seconds.
Returns:
- dict or None: The loaded provider data or None if the operation fails.
"""
current_time = time.time()
if cache_file.exists() and (current_time - cache_file.stat().st_mtime) < cache_expiry:
data = read_cache_file(cache_file)
if data:
return data
click.secho("Cache is corrupted. Fetching provider data from the web...", fg="yellow")
else:
click.secho("Cache expired or not found. Fetching provider data from the web...", fg="cyan")
return fetch_provider_data(cache_file)
def read_cache_file(cache_file):
"""
Reads and returns the JSON content from a cache file. Returns None if the file contains invalid JSON.
Args:
- cache_file (Path): The path to the cache file.
Returns:
- dict or None: The JSON content of the cache file or None if the JSON is invalid.
"""
try:
with open(cache_file, "r") as f:
return json.load(f)
except json.JSONDecodeError:
return None
def fetch_provider_data(cache_file):
"""
Fetches provider data from a specified URL and caches it to a file.
Args:
- cache_file (Path): The path to the cache file.
Returns:
- dict or None: The fetched provider data or None if the operation fails.
"""
try:
response = requests.get(JSON_URL, stream=True, timeout=10)
response.raise_for_status()
data = download_data(response)
with open(cache_file, "w") as f:
json.dump(data, f)
return data
except requests.RequestException as e:
click.secho(f"Error fetching provider data: {e}", fg="red")
except json.JSONDecodeError:
click.secho("Error parsing provider data. Invalid JSON format.", fg="red")
return None
def download_data(response):
"""
Downloads data from a given HTTP response and returns the JSON content.
Args:
- response (requests.Response): The HTTP response object.
Returns:
- dict: The JSON content of the response.
"""
total_size = int(response.headers.get('content-length', 0))
block_size = 8192
data_chunks = []
with click.progressbar(length=total_size, label='Downloading', show_pos=True) as progress_bar:
for chunk in response.iter_content(block_size):
if chunk:
data_chunks.append(chunk)
progress_bar.update(len(chunk))
data_content = b''.join(data_chunks)
return json.loads(data_content.decode('utf-8'))
def get_provider_data():
"""
Retrieves provider data from a cache file, filters out models based on provider criteria, and returns a dictionary of providers mapped to their models.
Returns:
- dict or None: A dictionary of providers mapped to their models or None if the operation fails.
"""
cache_dir = Path.home() / '.crewai'
cache_dir.mkdir(exist_ok=True)
cache_file = cache_dir / 'provider_cache.json'
cache_expiry = 24 * 3600
data = load_provider_data(cache_file, cache_expiry)
if not data:
return None
provider_models = defaultdict(list)
for model_name, properties in data.items():
provider = properties.get("litellm_provider", "").strip().lower()
if 'http' in provider or provider == 'other':
continue
if provider:
provider_models[provider].append(model_name)
return provider_models

View File

@@ -1,4 +1,5 @@
import subprocess
import click
@@ -9,7 +10,7 @@ def replay_task_command(task_id: str) -> None:
Args:
task_id (str): The ID of the task to replay from.
"""
command = ["poetry", "run", "replay", task_id]
command = ["uv", "run", "replay", task_id]
try:
result = subprocess.run(command, capture_output=False, text=True, check=True)

View File

@@ -1,23 +1,48 @@
import subprocess
import click
import tomllib
from packaging import version
from crewai.cli.utils import get_crewai_version
def run_crew() -> None:
"""
Run the crew by running a command in the Poetry environment.
Run the crew by running a command in the UV environment.
"""
command = ["poetry", "run", "run_crew"]
command = ["uv", "run", "run_crew"]
crewai_version = get_crewai_version()
min_required_version = "0.71.0"
with open("pyproject.toml", "rb") as f:
data = tomllib.load(f)
if data.get("tool", {}).get("poetry") and (
version.parse(crewai_version) < version.parse(min_required_version)
):
click.secho(
f"You are running an older version of crewAI ({crewai_version}) that uses poetry pyproject.toml. "
f"Please run `crewai update` to update your pyproject.toml to use uv.",
fg="red",
)
print()
try:
result = subprocess.run(command, capture_output=False, text=True, check=True)
if result.stderr:
click.echo(result.stderr, err=True)
subprocess.run(command, capture_output=False, text=True, check=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)
click.echo(e.output, err=True, nl=True)
with open("pyproject.toml", "rb") as f:
data = tomllib.load(f)
if data.get("tool", {}).get("poetry"):
click.secho(
"It's possible that you are using an old version of crewAI that uses poetry, please run `crewai update` to update your pyproject.toml to use uv.",
fg="yellow",
)
except Exception as e:
click.echo(f"An unexpected error occurred: {e}", err=True)

View File

@@ -5,9 +5,9 @@ import click
def run_flow() -> None:
"""
Run the flow by running a command in the Poetry environment.
Run the flow by running a command in the UV environment.
"""
command = ["poetry", "run", "run_flow"]
command = ["uv", "run", "run_flow"]
try:
result = subprocess.run(command, capture_output=False, text=True, check=True)

View File

@@ -4,17 +4,17 @@ Welcome to the {{crew_name}} Crew project, powered by [crewAI](https://crewai.co
## Installation
Ensure you have Python >=3.10 <=3.13 installed on your system. This project uses [Poetry](https://python-poetry.org/) for dependency management and package handling, offering a seamless setup and execution experience.
Ensure you have Python >=3.10 <=3.13 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
First, if you haven't already, install Poetry:
First, if you haven't already, install uv:
```bash
pip install poetry
pip install uv
```
Next, navigate to your project directory and install the dependencies:
1. First lock the dependencies and install them by using the CLI command:
(Optional) Lock the dependencies and install them by using the CLI command:
```bash
crewai install
```

View File

@@ -2,7 +2,7 @@
import sys
from {{folder_name}}.crew import {{crew_name}}Crew
# This main file is intended to be a way for your to run your
# This main file is intended to be a way for you to run your
# crew locally, so refrain from adding necessary logic into this file.
# Replace with inputs you want to test with, it will automatically
# interpolate any tasks and agents information

View File

@@ -1,15 +1,14 @@
[tool.poetry]
[project]
name = "{{folder_name}}"
version = "0.1.0"
description = "{{name}} using crewAI"
authors = ["Your Name <you@example.com>"]
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<=3.13"
dependencies = [
"crewai[tools]>=0.67.1,<1.0.0"
]
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
crewai = { extras = ["tools"], version = ">=0.70.1,<1.0.0" }
[tool.poetry.scripts]
[project.scripts]
{{folder_name}} = "{{folder_name}}.main:run"
run_crew = "{{folder_name}}.main:run"
train = "{{folder_name}}.main:train"
@@ -17,5 +16,5 @@ replay = "{{folder_name}}.main:replay"
test = "{{folder_name}}.main:test"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
requires = ["hatchling"]
build-backend = "hatchling.build"

View File

@@ -4,18 +4,17 @@ Welcome to the {{crew_name}} Crew project, powered by [crewAI](https://crewai.co
## Installation
Ensure you have Python >=3.10 <=3.13 installed on your system. This project uses [Poetry](https://python-poetry.org/) for dependency management and package handling, offering a seamless setup and execution experience.
Ensure you have Python >=3.10 <=3.13 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
First, if you haven't already, install Poetry:
First, if you haven't already, install uv:
```bash
pip install poetry
pip install uv
```
Next, navigate to your project directory and install the dependencies:
1. First lock the dependencies and then install them:
(Optional) Lock the dependencies and install them by using the CLI command:
```bash
crewai install
```

View File

@@ -1,19 +1,19 @@
[tool.poetry]
[project]
name = "{{folder_name}}"
version = "0.1.0"
description = "{{name}} using crewAI"
authors = ["Your Name <you@example.com>"]
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<=3.13"
dependencies = [
"crewai[tools]>=0.67.1,<1.0.0",
"asyncio"
]
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
crewai = { extras = ["tools"], version = ">=0.70.1,<1.0.0" }
asyncio = "*"
[tool.poetry.scripts]
[project.scripts]
{{folder_name}} = "{{folder_name}}.main:main"
run_flow = "{{folder_name}}.main:main"
plot_flow = "{{folder_name}}.main:plot"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
requires = ["hatchling"]
build-backend = "hatchling.build"

View File

@@ -1,20 +1,21 @@
[tool.poetry]
[project]
name = "{{folder_name}}"
version = "0.1.0"
description = "{{name}} using crewAI"
authors = ["Your Name <you@example.com>"]
requires-python = ">=3.10,<=3.13"
dependencies = [
"crewai[tools]>=0.67.1,<1.0.0"
]
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
crewai = { extras = ["tools"], version = ">=0.70.1,<1.0.0" }
[tool.poetry.scripts]
[project.scripts]
{{folder_name}} = "{{folder_name}}.main:main"
run_crew = "{{folder_name}}.main:main"
train = "{{folder_name}}.main:train"
replay = "{{folder_name}}.main:replay"
test = "{{folder_name}}.main:test"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
requires = ["hatchling"]
build-backend = "hatchling.build"

View File

@@ -0,0 +1,10 @@
# Python-generated files
__pycache__/
*.py[oc]
build/
dist/
wheels/
*.egg-info
# Virtual environments
.venv

View File

@@ -6,13 +6,13 @@ custom tools to power up your crews.
## Installing
Ensure you have Python >=3.10 <=3.13 installed on your system. This project
uses [Poetry](https://python-poetry.org/) for dependency management and package
uses [UV](https://docs.astral.sh/uv/) for dependency management and package
handling, offering a seamless setup and execution experience.
First, if you haven't already, install Poetry:
First, if you haven't already, install `uv`:
```bash
pip install poetry
pip install uv
```
Next, navigate to your project directory and install the dependencies with:

View File

@@ -1,14 +1,10 @@
[tool.poetry]
[project]
name = "{{folder_name}}"
version = "0.1.0"
description = "Power up your crews with {{folder_name}}"
authors = ["Your Name <you@example.com>"]
readme = "README.md"
requires-python = ">=3.10,<=3.13"
dependencies = [
"crewai[tools]>=0.70.1"
]
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
crewai = { extras = ["tools"], version = ">=0.70.1,<1.0.0" }
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

View File

@@ -1,20 +1,24 @@
import base64
from pathlib import Path
import click
import os
import platform
import subprocess
import tempfile
from pathlib import Path
from netrc import netrc
import stat
import click
from rich.console import Console
from crewai.cli.command import BaseCommand, PlusAPIMixin
from crewai.cli import git
from crewai.cli.command import BaseCommand, PlusAPIMixin
from crewai.cli.utils import (
get_project_name,
get_project_description,
get_project_name,
get_project_version,
tree_copy,
tree_find_and_replace,
)
from rich.console import Console
console = Console()
@@ -24,6 +28,8 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
A class to handle tool repository related operations for CrewAI projects.
"""
BASE_URL = "https://app.crewai.com/pypi/"
def __init__(self):
BaseCommand.__init__(self)
PlusAPIMixin.__init__(self, telemetry=self._telemetry)
@@ -82,7 +88,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
with tempfile.TemporaryDirectory() as temp_build_dir:
subprocess.run(
["poetry", "build", "-f", "sdist", "--output", temp_build_dir],
["uv", "build", "--sdist", "--out-dir", temp_build_dir],
check=True,
capture_output=False,
)
@@ -92,7 +98,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
)
if not tarball_filename:
console.print(
"Project build failed. Please ensure that the command `poetry build -f sdist` completes successfully.",
"Project build failed. Please ensure that the command `uv build --sdist` completes successfully.",
style="bold red",
)
raise SystemExit
@@ -143,68 +149,41 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
if login_response.status_code != 200:
console.print(
"Failed to authenticate to the tool repository. Make sure you have the access to tools.",
"Authentication failed. Verify access to the tool repository, or try `crewai login`. ",
style="bold red",
)
raise SystemExit
login_response_json = login_response.json()
for repository in login_response_json["repositories"]:
self._add_repository_to_poetry(
repository, login_response_json["credential"]
)
self._set_netrc_credentials(login_response_json["credential"])
console.print(
"Succesfully authenticated to the tool repository.", style="bold green"
"Successfully authenticated to the tool repository.", style="bold green"
)
def _add_repository_to_poetry(self, repository, credentials):
repository_handle = f"crewai-{repository['handle']}"
def _set_netrc_credentials(self, credentials, netrc_path=None):
if not netrc_path:
netrc_filename = "_netrc" if platform.system() == "Windows" else ".netrc"
netrc_path = Path.home() / netrc_filename
netrc_path.touch(mode=stat.S_IRUSR | stat.S_IWUSR, exist_ok=True)
add_repository_command = [
"poetry",
"source",
"add",
"--priority=explicit",
repository_handle,
repository["url"],
]
add_repository_result = subprocess.run(
add_repository_command, text=True, check=True
)
netrc_instance = netrc(file=netrc_path)
netrc_instance.hosts["app.crewai.com"] = (credentials["username"], "", credentials["password"])
if add_repository_result.stderr:
click.echo(add_repository_result.stderr, err=True)
raise SystemExit
with open(netrc_path, 'w') as file:
file.write(str(netrc_instance))
add_repository_credentials_command = [
"poetry",
"config",
f"http-basic.{repository_handle}",
credentials["username"],
credentials["password"],
]
add_repository_credentials_result = subprocess.run(
add_repository_credentials_command,
capture_output=False,
text=True,
check=True,
)
if add_repository_credentials_result.stderr:
click.echo(add_repository_credentials_result.stderr, err=True)
raise SystemExit
console.print(f"Added credentials to {netrc_path}", style="bold green")
def _add_package(self, tool_details):
tool_handle = tool_details["handle"]
repository_handle = tool_details["repository"]["handle"]
pypi_index_handle = f"crewai-{repository_handle}"
add_package_command = [
"poetry",
"uv",
"add",
"--source",
pypi_index_handle,
"--extra-index-url",
self.BASE_URL + repository_handle,
tool_handle,
]
add_package_result = subprocess.run(

View File

@@ -5,12 +5,12 @@ import click
def train_crew(n_iterations: int, filename: str) -> None:
"""
Train the crew by running a command in the Poetry environment.
Train the crew by running a command in the UV environment.
Args:
n_iterations (int): The number of iterations to train the crew.
"""
command = ["poetry", "run", "train", str(n_iterations), filename]
command = ["uv", "run", "train", str(n_iterations), filename]
try:
if n_iterations <= 0:

View File

@@ -0,0 +1,115 @@
import shutil
import tomli_w
import tomllib
def update_crew() -> None:
"""Update the pyproject.toml of the Crew project to use uv."""
migrate_pyproject("pyproject.toml", "pyproject.toml")
def migrate_pyproject(input_file, output_file):
"""
Migrate the pyproject.toml to the new format.
This function is used to migrate the pyproject.toml to the new format.
And it will be used to migrate the pyproject.toml to the new format when uv is used.
When the time comes that uv supports the new format, this function will be deprecated.
"""
# Read the input pyproject.toml
with open(input_file, "rb") as f:
pyproject = tomllib.load(f)
# Initialize the new project structure
new_pyproject = {
"project": {},
"build-system": {"requires": ["hatchling"], "build-backend": "hatchling.build"},
}
# Migrate project metadata
if "tool" in pyproject and "poetry" in pyproject["tool"]:
poetry = pyproject["tool"]["poetry"]
new_pyproject["project"]["name"] = poetry.get("name")
new_pyproject["project"]["version"] = poetry.get("version")
new_pyproject["project"]["description"] = poetry.get("description")
new_pyproject["project"]["authors"] = [
{
"name": author.split("<")[0].strip(),
"email": author.split("<")[1].strip(">").strip(),
}
for author in poetry.get("authors", [])
]
new_pyproject["project"]["requires-python"] = poetry.get("python")
else:
# If it's already in the new format, just copy the project section
new_pyproject["project"] = pyproject.get("project", {})
# Migrate or copy dependencies
if "dependencies" in new_pyproject["project"]:
# If dependencies are already in the new format, keep them as is
pass
elif "dependencies" in poetry:
new_pyproject["project"]["dependencies"] = []
for dep, version in poetry["dependencies"].items():
if isinstance(version, dict): # Handle extras
extras = ",".join(version.get("extras", []))
new_dep = f"{dep}[{extras}]"
if "version" in version:
new_dep += parse_version(version["version"])
elif dep == "python":
new_pyproject["project"]["requires-python"] = version
continue
else:
new_dep = f"{dep}{parse_version(version)}"
new_pyproject["project"]["dependencies"].append(new_dep)
# Migrate or copy scripts
if "scripts" in poetry:
new_pyproject["project"]["scripts"] = poetry["scripts"]
elif "scripts" in pyproject.get("project", {}):
new_pyproject["project"]["scripts"] = pyproject["project"]["scripts"]
else:
new_pyproject["project"]["scripts"] = {}
if (
"run_crew" not in new_pyproject["project"]["scripts"]
and len(new_pyproject["project"]["scripts"]) > 0
):
# Extract the module name from any existing script
existing_scripts = new_pyproject["project"]["scripts"]
module_name = next(
(value.split(".")[0] for value in existing_scripts.values() if "." in value)
)
new_pyproject["project"]["scripts"]["run_crew"] = f"{module_name}.main:run"
# Migrate optional dependencies
if "extras" in poetry:
new_pyproject["project"]["optional-dependencies"] = poetry["extras"]
# Backup the old pyproject.toml
backup_file = "pyproject-old.toml"
shutil.copy2(input_file, backup_file)
print(f"Original pyproject.toml backed up as {backup_file}")
# Write the new pyproject.toml
with open(output_file, "wb") as f:
tomli_w.dump(new_pyproject, f)
print(f"Migration complete. New pyproject.toml written to {output_file}")
def parse_version(version: str) -> str:
"""Parse and convert version specifiers."""
if version.startswith("^"):
main_lib_version = version[1:].split(",")[0]
addtional_lib_version = None
if len(version[1:].split(",")) > 1:
addtional_lib_version = version[1:].split(",")[1]
return f">={main_lib_version}" + (
f",{addtional_lib_version}" if addtional_lib_version else ""
)
return version

View File

@@ -1,13 +1,15 @@
import importlib.metadata
import os
import shutil
import click
import sys
import importlib.metadata
from functools import reduce
from typing import Any, Dict, List
import click
from rich.console import Console
from crewai.cli.authentication.utils import TokenManager
from functools import reduce
from rich.console import Console
from typing import Any, Dict, List
from crewai.cli.constants import ENV_VARS
if sys.version_info >= (3, 11):
import tomllib
@@ -55,17 +57,14 @@ def simple_toml_parser(content):
def parse_toml(content):
if sys.version_info >= (3, 11):
return tomllib.loads(content)
else:
return simple_toml_parser(content)
return simple_toml_parser(content)
def get_project_name(
pyproject_path: str = "pyproject.toml", require: bool = False
) -> str | None:
"""Get the project name from the pyproject.toml file."""
return _get_project_attribute(
pyproject_path, ["tool", "poetry", "name"], require=require
)
return _get_project_attribute(pyproject_path, ["project", "name"], require=require)
def get_project_version(
@@ -73,7 +72,7 @@ def get_project_version(
) -> str | None:
"""Get the project version from the pyproject.toml file."""
return _get_project_attribute(
pyproject_path, ["tool", "poetry", "version"], require=require
pyproject_path, ["project", "version"], require=require
)
@@ -82,7 +81,7 @@ def get_project_description(
) -> str | None:
"""Get the project description from the pyproject.toml file."""
return _get_project_attribute(
pyproject_path, ["tool", "poetry", "description"], require=require
pyproject_path, ["project", "description"], require=require
)
@@ -97,10 +96,9 @@ def _get_project_attribute(
pyproject_content = parse_toml(f.read())
dependencies = (
_get_nested_value(pyproject_content, ["tool", "poetry", "dependencies"])
or {}
_get_nested_value(pyproject_content, ["project", "dependencies"]) or []
)
if "crewai" not in dependencies:
if not any(True for dep in dependencies if "crewai" in dep):
raise Exception("crewai is not in the dependencies.")
attribute = _get_nested_value(pyproject_content, keys)
@@ -203,3 +201,76 @@ def tree_find_and_replace(directory, find, replace):
new_dirpath = os.path.join(path, new_dirname)
old_dirpath = os.path.join(path, dirname)
os.rename(old_dirpath, new_dirpath)
def load_env_vars(folder_path):
"""
Loads environment variables from a .env file in the specified folder path.
Args:
- folder_path (Path): The path to the folder containing the .env file.
Returns:
- dict: A dictionary of environment variables.
"""
env_file_path = folder_path / ".env"
env_vars = {}
if env_file_path.exists():
with open(env_file_path, "r") as file:
for line in file:
key, _, value = line.strip().partition("=")
if key and value:
env_vars[key] = value
return env_vars
def update_env_vars(env_vars, provider, model):
"""
Updates environment variables with the API key for the selected provider and model.
Args:
- env_vars (dict): Environment variables dictionary.
- provider (str): Selected provider.
- model (str): Selected model.
Returns:
- None
"""
api_key_var = ENV_VARS.get(
provider,
[
click.prompt(
f"Enter the environment variable name for your {provider.capitalize()} API key",
type=str,
)
],
)[0]
if api_key_var not in env_vars:
try:
env_vars[api_key_var] = click.prompt(
f"Enter your {provider.capitalize()} API key", type=str, hide_input=True
)
except click.exceptions.Abort:
click.secho("Operation aborted by the user.", fg="red")
return None
else:
click.secho(f"API key already exists for {provider.capitalize()}.", fg="yellow")
env_vars["MODEL"] = model
click.secho(f"Selected model: {model}", fg="green")
return env_vars
def write_env_file(folder_path, env_vars):
"""
Writes environment variables to a .env file in the specified folder.
Args:
- folder_path (Path): The path to the folder where the .env file will be written.
- env_vars (dict): A dictionary of environment variables to write.
"""
env_file_path = folder_path / ".env"
with open(env_file_path, "w") as file:
for key, value in env_vars.items():
file.write(f"{key}={value}\n")

View File

@@ -15,7 +15,10 @@ class EntityMemory(Memory):
storage
if storage
else RAGStorage(
type="entities", allow_reset=False, embedder_config=embedder_config, crew=crew
type="entities",
allow_reset=False,
embedder_config=embedder_config,
crew=crew,
)
)
super().__init__(storage)

View File

@@ -59,7 +59,7 @@ class ToolUsage:
agent: Any,
action: Any,
) -> None:
self._i18n: I18N = I18N()
self._i18n: I18N = agent.i18n
self._printer: Printer = Printer()
self._telemetry: Telemetry = Telemetry()
self._run_attempts: int = 1

View File

@@ -20,7 +20,8 @@
"getting_input": "This is the agent's final answer: {final_answer}\n\n",
"summarizer_system_message": "You are a helpful assistant that summarizes text.",
"sumamrize_instruction": "Summarize the following text, make sure to include all the important information: {group}",
"summary": "This is a summary of our conversation so far:\n{merged_summary}"
"summary": "This is a summary of our conversation so far:\n{merged_summary}",
"manager_request": "Your best answer to your coworker asking you this, accounting for the context shared."
},
"errors": {
"force_final_answer_error": "You can't keep going, this was the best you could do.\n {formatted_answer.text}",

View File

@@ -1,21 +1,21 @@
"""Test Agent creation and execution basic functionality."""
import os
from unittest import mock
from unittest.mock import patch
import os
import pytest
from crewai_tools import tool
from crewai import Agent, Crew, Task
from crewai.agents.cache import CacheHandler
from crewai.agents.crew_agent_executor import CrewAgentExecutor
from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException
from crewai.llm import LLM
from crewai.agents.parser import CrewAgentParser, OutputParserException
from crewai.tools.tool_calling import InstructorToolCalling
from crewai.tools.tool_usage import ToolUsage
from crewai.tools.tool_usage_events import ToolUsageFinished
from crewai.utilities import RPMController
from crewai_tools import tool
from crewai.agents.parser import AgentAction
from crewai.utilities.events import Emitter
@@ -73,7 +73,7 @@ def test_agent_creation():
def test_agent_default_values():
agent = Agent(role="test role", goal="test goal", backstory="test backstory")
assert agent.llm.model == "gpt-4o"
assert agent.llm.model == "gpt-4o-mini"
assert agent.allow_delegation is False
@@ -116,6 +116,7 @@ def test_custom_llm_temperature_preservation():
@pytest.mark.vcr(filter_headers=["authorization"])
def test_agent_execute_task():
from langchain_openai import ChatOpenAI
from crewai import Task
agent = Agent(
@@ -206,7 +207,7 @@ def test_logging_tool_usage():
verbose=True,
)
assert agent.llm.model == "gpt-4o"
assert agent.llm.model == "gpt-4o-mini"
assert agent.tools_handler.last_used_tool == {}
task = Task(
description="What is 3 times 4?",
@@ -602,6 +603,7 @@ def test_agent_respect_the_max_rpm_set(capsys):
@pytest.mark.vcr(filter_headers=["authorization"])
def test_agent_respect_the_max_rpm_set_over_crew_rpm(capsys):
from unittest.mock import patch
from crewai_tools import tool
@tool
@@ -693,6 +695,7 @@ def test_agent_without_max_rpm_respet_crew_rpm(capsys):
@pytest.mark.vcr(filter_headers=["authorization"])
def test_agent_error_on_parsing_tool(capsys):
from unittest.mock import patch
from crewai_tools import tool
@tool
@@ -855,7 +858,9 @@ def test_agent_function_calling_llm():
tasks = [essay]
crew = Crew(agents=[agent1], tasks=tasks)
from unittest.mock import patch
import instructor
from crewai.tools.tool_usage import ToolUsage
with patch.object(

View File

@@ -1,12 +1,12 @@
import pytest
import requests
import sys
import unittest
from io import StringIO
from requests.exceptions import JSONDecodeError
from unittest.mock import MagicMock, Mock, patch
import pytest
import requests
from requests.exceptions import JSONDecodeError
from crewai.cli.deploy.main import DeployCommand
from crewai.cli.utils import parse_toml
@@ -228,13 +228,11 @@ class TestDeployCommand(unittest.TestCase):
"builtins.open",
new_callable=unittest.mock.mock_open,
read_data="""
[tool.poetry]
[project]
name = "test_project"
version = "0.1.0"
[tool.poetry.dependencies]
python = "^3.10"
crewai = { extras = ["tools"], version = ">=0.51.0,<1.0.0" }
requires-python = ">=3.10,<=3.13"
dependencies = ["crewai"]
""",
)
def test_get_project_name_python_310(self, mock_open):
@@ -248,13 +246,11 @@ class TestDeployCommand(unittest.TestCase):
"builtins.open",
new_callable=unittest.mock.mock_open,
read_data="""
[tool.poetry]
[project]
name = "test_project"
version = "0.1.0"
[tool.poetry.dependencies]
python = "^3.11"
crewai = { extras = ["tools"], version = ">=0.51.0,<1.0.0" }
requires-python = ">=3.10,<=3.13"
dependencies = ["crewai"]
""",
)
def test_get_project_name_python_311_plus(self, mock_open):

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@@ -18,12 +18,12 @@ from crewai.cli import evaluate_crew
def test_crew_success(mock_subprocess_run, n_iterations, model):
"""Test the crew function for successful execution."""
mock_subprocess_run.return_value = subprocess.CompletedProcess(
args=f"poetry run test {n_iterations} {model}", returncode=0
args=f"uv run test {n_iterations} {model}", returncode=0
)
result = evaluate_crew.evaluate_crew(n_iterations, model)
mock_subprocess_run.assert_called_once_with(
["poetry", "run", "test", str(n_iterations), model],
["uv", "run", "test", str(n_iterations), model],
capture_output=False,
text=True,
check=True,
@@ -55,14 +55,14 @@ def test_test_crew_called_process_error(mock_subprocess_run, click):
n_iterations = 5
mock_subprocess_run.side_effect = subprocess.CalledProcessError(
returncode=1,
cmd=["poetry", "run", "test", str(n_iterations), "gpt-4o"],
cmd=["uv", "run", "test", str(n_iterations), "gpt-4o"],
output="Error",
stderr="Some error occurred",
)
evaluate_crew.evaluate_crew(n_iterations, "gpt-4o")
mock_subprocess_run.assert_called_once_with(
["poetry", "run", "test", "5", "gpt-4o"],
["uv", "run", "test", "5", "gpt-4o"],
capture_output=False,
text=True,
check=True,
@@ -70,7 +70,7 @@ def test_test_crew_called_process_error(mock_subprocess_run, click):
click.echo.assert_has_calls(
[
mock.call.echo(
"An error occurred while testing the crew: Command '['poetry', 'run', 'test', '5', 'gpt-4o']' returned non-zero exit status 1.",
"An error occurred while testing the crew: Command '['uv', 'run', 'test', '5', 'gpt-4o']' returned non-zero exit status 1.",
err=True,
),
mock.call.echo("Error", err=True),
@@ -87,7 +87,7 @@ def test_test_crew_unexpected_exception(mock_subprocess_run, click):
evaluate_crew.evaluate_crew(n_iterations, "gpt-4o")
mock_subprocess_run.assert_called_once_with(
["poetry", "run", "test", "5", "gpt-4o"],
["uv", "run", "test", "5", "gpt-4o"],
capture_output=False,
text=True,
check=True,

View File

@@ -92,16 +92,20 @@ class TestPlusAPI(unittest.TestCase):
)
self.assertEqual(response, mock_response)
@patch("crewai.cli.plus_api.requests.request")
def test_make_request(self, mock_request):
@patch("crewai.cli.plus_api.requests.Session")
def test_make_request(self, mock_session):
mock_response = MagicMock()
mock_request.return_value = mock_response
mock_session_instance = mock_session.return_value
mock_session_instance.request.return_value = mock_response
response = self.api._make_request("GET", "test_endpoint")
mock_request.assert_called_once_with(
mock_session.assert_called_once()
mock_session_instance.request.assert_called_once_with(
"GET", f"{self.api.base_url}/test_endpoint", headers=self.api.headers
)
mock_session_instance.trust_env = False
self.assertEqual(response, mock_response)
@patch("crewai.cli.plus_api.PlusAPI._make_request")

View File

@@ -1,13 +1,16 @@
import os
import tempfile
import unittest
import unittest.mock
import os
from contextlib import contextmanager
from io import StringIO
from unittest import mock
from unittest.mock import MagicMock, patch
from pytest import raises
from crewai.cli.tools.main import ToolCommand
from io import StringIO
from unittest.mock import patch, MagicMock
@contextmanager
def in_temp_dir():
@@ -19,6 +22,7 @@ def in_temp_dir():
finally:
os.chdir(original_dir)
@patch("crewai.cli.tools.main.subprocess.run")
def test_create_success(mock_subprocess):
with in_temp_dir():
@@ -38,9 +42,7 @@ def test_create_success(mock_subprocess):
)
assert os.path.isfile(os.path.join("test_tool", "src", "test_tool", "tool.py"))
with open(
os.path.join("test_tool", "src", "test_tool", "tool.py"), "r"
) as f:
with open(os.path.join("test_tool", "src", "test_tool", "tool.py"), "r") as f:
content = f.read()
assert "class TestTool" in content
@@ -49,6 +51,7 @@ def test_create_success(mock_subprocess):
assert "Creating custom tool test_tool..." in output
@patch("crewai.cli.tools.main.subprocess.run")
@patch("crewai.cli.plus_api.PlusAPI.get_tool")
def test_install_success(mock_get, mock_subprocess_run):
@@ -67,9 +70,15 @@ def test_install_success(mock_get, mock_subprocess_run):
tool_command.install("sample-tool")
output = fake_out.getvalue()
mock_get.assert_called_once_with("sample-tool")
mock_get.assert_has_calls([mock.call("sample-tool"), mock.call().json()])
mock_subprocess_run.assert_any_call(
["poetry", "add", "--source", "crewai-sample-repo", "sample-tool"],
[
"uv",
"add",
"--extra-index-url",
"https://app.crewai.com/pypi/sample-repo",
"sample-tool",
],
capture_output=False,
text=True,
check=True,
@@ -77,6 +86,7 @@ def test_install_success(mock_get, mock_subprocess_run):
assert "Succesfully installed sample-tool" in output
@patch("crewai.cli.plus_api.PlusAPI.get_tool")
def test_install_tool_not_found(mock_get):
mock_get_response = MagicMock()
@@ -95,6 +105,7 @@ def test_install_tool_not_found(mock_get):
mock_get.assert_called_once_with("non-existent-tool")
assert "No tool found with this name" in output
@patch("crewai.cli.plus_api.PlusAPI.get_tool")
def test_install_api_error(mock_get):
mock_get_response = MagicMock()
@@ -113,15 +124,16 @@ def test_install_api_error(mock_get):
mock_get.assert_called_once_with("error-tool")
assert "Failed to get tool details" in output
@patch("crewai.cli.tools.main.git.Repository.is_synced", return_value=False)
def test_publish_when_not_in_sync(mock_is_synced):
with patch("sys.stdout", new=StringIO()) as fake_out, \
raises(SystemExit):
with patch("sys.stdout", new=StringIO()) as fake_out, raises(SystemExit):
tool_command = ToolCommand()
tool_command.publish(is_public=True)
assert "Local changes need to be resolved before publishing" in fake_out.getvalue()
@patch("crewai.cli.tools.main.get_project_name", return_value="sample-tool")
@patch("crewai.cli.tools.main.get_project_version", return_value="1.0.0")
@patch("crewai.cli.tools.main.get_project_description", return_value="A sample tool")
@@ -156,7 +168,7 @@ def test_publish_when_not_in_sync_and_force(
mock_get_project_version.assert_called_with(require=True)
mock_get_project_description.assert_called_with(require=False)
mock_subprocess_run.assert_called_with(
["poetry", "build", "-f", "sdist", "--output", unittest.mock.ANY],
["uv", "build", "--sdist", "--out-dir", unittest.mock.ANY],
check=True,
capture_output=False,
)
@@ -169,6 +181,7 @@ def test_publish_when_not_in_sync_and_force(
encoded_file=unittest.mock.ANY,
)
@patch("crewai.cli.tools.main.get_project_name", return_value="sample-tool")
@patch("crewai.cli.tools.main.get_project_version", return_value="1.0.0")
@patch("crewai.cli.tools.main.get_project_description", return_value="A sample tool")
@@ -203,7 +216,7 @@ def test_publish_success(
mock_get_project_version.assert_called_with(require=True)
mock_get_project_description.assert_called_with(require=False)
mock_subprocess_run.assert_called_with(
["poetry", "build", "-f", "sdist", "--output", unittest.mock.ANY],
["uv", "build", "--sdist", "--out-dir", unittest.mock.ANY],
check=True,
capture_output=False,
)
@@ -216,6 +229,7 @@ def test_publish_success(
encoded_file=unittest.mock.ANY,
)
@patch("crewai.cli.tools.main.get_project_name", return_value="sample-tool")
@patch("crewai.cli.tools.main.get_project_version", return_value="1.0.0")
@patch("crewai.cli.tools.main.get_project_description", return_value="A sample tool")
@@ -254,6 +268,7 @@ def test_publish_failure(
assert "Failed to complete operation" in output
assert "Name is already taken" in output
@patch("crewai.cli.tools.main.get_project_name", return_value="sample-tool")
@patch("crewai.cli.tools.main.get_project_version", return_value="1.0.0")
@patch("crewai.cli.tools.main.get_project_description", return_value="A sample tool")
@@ -291,54 +306,3 @@ def test_publish_api_error(
mock_publish.assert_called_once()
assert "Request to Enterprise API failed" in output
@patch("crewai.cli.plus_api.PlusAPI.login_to_tool_repository")
@patch("crewai.cli.tools.main.subprocess.run")
def test_login_success(mock_subprocess_run, mock_login):
mock_login_response = MagicMock()
mock_login_response.status_code = 200
mock_login_response.json.return_value = {
"repositories": [
{
"handle": "tools",
"url": "https://example.com/repo",
}
],
"credential": {"username": "user", "password": "pass"},
}
mock_login.return_value = mock_login_response
mock_subprocess_run.return_value = MagicMock(stderr=None)
tool_command = ToolCommand()
with patch("sys.stdout", new=StringIO()) as fake_out:
tool_command.login()
output = fake_out.getvalue()
mock_login.assert_called_once()
mock_subprocess_run.assert_any_call(
[
"poetry",
"source",
"add",
"--priority=explicit",
"crewai-tools",
"https://example.com/repo",
],
text=True,
check=True,
)
mock_subprocess_run.assert_any_call(
[
"poetry",
"config",
"http-basic.crewai-tools",
"user",
"pass",
],
capture_output=False,
text=True,
check=True,
)
assert "Succesfully authenticated to the tool repository" in output

View File

@@ -8,7 +8,7 @@ from crewai.cli.train_crew import train_crew
def test_train_crew_positive_iterations(mock_subprocess_run):
n_iterations = 5
mock_subprocess_run.return_value = subprocess.CompletedProcess(
args=["poetry", "run", "train", str(n_iterations)],
args=["uv", "run", "train", str(n_iterations)],
returncode=0,
stdout="Success",
stderr="",
@@ -17,7 +17,7 @@ def test_train_crew_positive_iterations(mock_subprocess_run):
train_crew(n_iterations, "trained_agents_data.pkl")
mock_subprocess_run.assert_called_once_with(
["poetry", "run", "train", str(n_iterations), "trained_agents_data.pkl"],
["uv", "run", "train", str(n_iterations), "trained_agents_data.pkl"],
capture_output=False,
text=True,
check=True,
@@ -48,14 +48,14 @@ def test_train_crew_called_process_error(mock_subprocess_run, click):
n_iterations = 5
mock_subprocess_run.side_effect = subprocess.CalledProcessError(
returncode=1,
cmd=["poetry", "run", "train", str(n_iterations)],
cmd=["uv", "run", "train", str(n_iterations)],
output="Error",
stderr="Some error occurred",
)
train_crew(n_iterations, "trained_agents_data.pkl")
mock_subprocess_run.assert_called_once_with(
["poetry", "run", "train", str(n_iterations), "trained_agents_data.pkl"],
["uv", "run", "train", str(n_iterations), "trained_agents_data.pkl"],
capture_output=False,
text=True,
check=True,
@@ -63,7 +63,7 @@ def test_train_crew_called_process_error(mock_subprocess_run, click):
click.echo.assert_has_calls(
[
mock.call.echo(
"An error occurred while training the crew: Command '['poetry', 'run', 'train', '5']' returned non-zero exit status 1.",
"An error occurred while training the crew: Command '['uv', 'run', 'train', '5']' returned non-zero exit status 1.",
err=True,
),
mock.call.echo("Error", err=True),
@@ -79,7 +79,7 @@ def test_train_crew_unexpected_exception(mock_subprocess_run, click):
train_crew(n_iterations, "trained_agents_data.pkl")
mock_subprocess_run.assert_called_once_with(
["poetry", "run", "train", str(n_iterations), "trained_agents_data.pkl"],
["uv", "run", "train", str(n_iterations), "trained_agents_data.pkl"],
capture_output=False,
text=True,
check=True,

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