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8 Commits

Author SHA1 Message Date
Devin AI
f28e3e0be8 Fix lint error: remove unused 're' import from test file
Co-Authored-By: João <joao@crewai.com>
2025-06-24 06:21:34 +00:00
Devin AI
10a55bd210 Fix CLI documentation to reflect actual provider count and two-step process
- Update docs/concepts/cli.mdx to remove outdated 'top 5 most common LLM providers' reference
- Replace with accurate description of 12 available providers plus 'other' option
- Document the two-step process: select provider, then select model
- Add comprehensive test to prevent documentation drift in the future
- Test validates that docs stay in sync with actual CLI implementation

Fixes #3054

Co-Authored-By: João <joao@crewai.com>
2025-06-24 06:15:05 +00:00
Rostyslav Borovyk
c96d4a6823 Add Oxylabs Web Scraping tools (#2905)
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* Add Oxylabs tools

* Review updates

* Review updates

---------

Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
2025-06-23 13:58:16 -04:00
Lucas Gomide
59032817c7 docs: update recommendation filters for MCP and Enterprise tools (#3041)
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2025-06-20 13:35:26 -04:00
Lucas Gomide
e9d8a853ea feat: support to initialize a tool from defined Tool attributes (#3023)
* feat: support to initialize a tool from defined Tool attributes

* fix: ensure Agent is able to load a list of Tools dynamically
2025-06-20 10:53:37 -04:00
Vidit Ostwal
463ea2b97f Fixed type annotation in task (#3021)
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* Added Union of List of Task, None, NotSpecified

* Seems like a flaky test

* Fixed run time issue

* Fixed Linting issues

* fix pydantic error

* aesthetic changes

---------

Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>
2025-06-19 14:37:46 -04:00
Jannik Maierhöfer
ec2903e5ee fix: upgrade langfuse code examples to langfuse python sdk v3 (#3030)
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Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
2025-06-19 12:18:33 -04:00
Daniel Barreto
4364585ebc Remove mkdocs from project dependencies (#3036)
CrewAI has been using https://mintlify.com/
to serve its docs
2025-06-19 11:21:08 -04:00
16 changed files with 384 additions and 552 deletions

View File

@@ -1,45 +0,0 @@
name: Deploy MkDocs
on:
release:
types: [published]
permissions:
contents: write
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Setup Python
uses: actions/setup-python@v5
with:
python-version: '3.10'
- name: Calculate requirements hash
id: req-hash
run: echo "::set-output name=hash::$(sha256sum requirements-doc.txt | awk '{print $1}')"
- name: Setup cache
uses: actions/cache@v4
with:
key: mkdocs-material-${{ steps.req-hash.outputs.hash }}
path: .cache
restore-keys: |
mkdocs-material-
- name: Install Requirements
run: |
sudo apt-get update &&
sudo apt-get install pngquant &&
pip install mkdocs-material mkdocs-material-extensions pillow cairosvg
env:
GH_TOKEN: ${{ secrets.GH_TOKEN }}
- name: Build and deploy MkDocs
run: mkdocs gh-deploy --force

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@@ -285,25 +285,32 @@ Watch this video tutorial for a step-by-step demonstration of deploying your cre
### 11. API Keys
When running ```crewai create crew``` command, the CLI will first show you the top 5 most common LLM providers and ask you to select one.
When running ```crewai create crew``` command, the CLI will show you a list of available LLM providers to choose from, followed by model selection for your chosen provider.
Once you've selected an LLM provider, you will be prompted for API keys.
Once you've selected an LLM provider and model, you will be prompted for API keys.
#### Initial API key providers
#### Available LLM Providers
The CLI will initially prompt for API keys for the following services:
The CLI will show you the following LLM providers to choose from:
* OpenAI
* Groq
* Anthropic
* Google Gemini
* NVIDIA NIM
* Groq
* Hugging Face
* Ollama
* Watson
* AWS Bedrock
* Azure
* Cerebras
* SambaNova
When you select a provider, the CLI will prompt you to enter your API key.
When you select a provider, the CLI will then show you available models for that provider and prompt you to enter your API key.
#### Other Options
If you select option 6, you will be able to select from a list of LiteLLM supported providers.
If you select "other", you will be able to select from a list of LiteLLM supported providers.
When you select a provider, the CLI will prompt you to enter the Key name and the API key.

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@@ -134,7 +134,7 @@
"tools/web-scraping/stagehandtool",
"tools/web-scraping/firecrawlcrawlwebsitetool",
"tools/web-scraping/firecrawlscrapewebsitetool",
"tools/web-scraping/firecrawlsearchtool"
"tools/web-scraping/oxylabsscraperstool"
]
},
{

View File

@@ -124,7 +124,7 @@ from crewai_tools import CrewaiEnterpriseTools
enterprise_tools = CrewaiEnterpriseTools(
actions_list=["gmail_find_email"] # only gmail_find_email tool will be available
)
gmail_tool = enterprise_tools[0]
gmail_tool = enterprise_tools["gmail_find_email"]
gmail_agent = Agent(
role="Gmail Manager",

View File

@@ -85,6 +85,22 @@ with MCPServerAdapter(server_params) as mcp_tools:
```
This general pattern shows how to integrate tools. For specific examples tailored to each transport, refer to the detailed guides below.
## Filtering Tools
```python
with MCPServerAdapter(server_params) as mcp_tools:
print(f"Available tools: {[tool.name for tool in mcp_tools]}")
my_agent = Agent(
role="MCP Tool User",
goal="Utilize tools from an MCP server.",
backstory="I can connect to MCP servers and use their tools.",
tools=mcp_tools["tool_name"], # Pass the loaded tools to your agent
reasoning=True,
verbose=True
)
# ... rest of your crew setup ...
```
## Explore MCP Integrations
<CardGroup cols={2}>

View File

@@ -30,18 +30,29 @@ Set your Langfuse API keys and configure OpenTelemetry export settings to send t
```python
import os
import base64
# Get keys for your project from the project settings page: https://cloud.langfuse.com
os.environ["LANGFUSE_PUBLIC_KEY"] = "pk-lf-..."
os.environ["LANGFUSE_SECRET_KEY"] = "sk-lf-..."
os.environ["LANGFUSE_HOST"] = "https://cloud.langfuse.com" # 🇪🇺 EU region
# os.environ["LANGFUSE_HOST"] = "https://us.cloud.langfuse.com" # 🇺🇸 US region
# Your OpenAI key
os.environ["OPENAI_API_KEY"] = "sk-proj-..."
```
With the environment variables set, we can now initialize the Langfuse client. get_client() initializes the Langfuse client using the credentials provided in the environment variables.
LANGFUSE_PUBLIC_KEY="pk-lf-..."
LANGFUSE_SECRET_KEY="sk-lf-..."
LANGFUSE_AUTH=base64.b64encode(f"{LANGFUSE_PUBLIC_KEY}:{LANGFUSE_SECRET_KEY}".encode()).decode()
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://cloud.langfuse.com/api/public/otel" # EU data region
# os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://us.cloud.langfuse.com/api/public/otel" # US data region
os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = f"Authorization=Basic {LANGFUSE_AUTH}"
# your openai key
os.environ["OPENAI_API_KEY"] = "sk-..."
```python
from langfuse import get_client
langfuse = get_client()
# Verify connection
if langfuse.auth_check():
print("Langfuse client is authenticated and ready!")
else:
print("Authentication failed. Please check your credentials and host.")
```
### Step 3: Initialize OpenLit

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@@ -56,6 +56,10 @@ These tools enable your agents to interact with the web, extract data from websi
<Card title="Stagehand Tool" icon="hand" href="/tools/web-scraping/stagehandtool">
Intelligent browser automation with natural language commands.
</Card>
<Card title="Oxylabs Scraper Tool" icon="globe" href="/tools/web-scraping/oxylabsscraperstool">
Access web data at scale with Oxylabs.
</Card>
</CardGroup>
## **Common Use Cases**
@@ -100,4 +104,4 @@ agent = Agent(
- **JavaScript-Heavy Sites**: Use `SeleniumScrapingTool` for dynamic content
- **Scale & Performance**: Use `FirecrawlScrapeWebsiteTool` for high-volume scraping
- **Cloud Infrastructure**: Use `BrowserBaseLoadTool` for scalable browser automation
- **Complex Workflows**: Use `StagehandTool` for intelligent browser interactions
- **Complex Workflows**: Use `StagehandTool` for intelligent browser interactions

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@@ -0,0 +1,236 @@
---
title: Oxylabs Scrapers
description: >
Oxylabs Scrapers allow to easily access the information from the respective sources. Please see the list of available sources below:
- `Amazon Product`
- `Amazon Search`
- `Google Seach`
- `Universal`
icon: globe
---
## Installation
Get the credentials by creating an Oxylabs Account [here](https://oxylabs.io).
```shell
pip install 'crewai[tools]' oxylabs
```
Check [Oxylabs Documentation](https://developers.oxylabs.io/scraping-solutions/web-scraper-api/targets) to get more information about API parameters.
# `OxylabsAmazonProductScraperTool`
### Example
```python
from crewai_tools import OxylabsAmazonProductScraperTool
# make sure OXYLABS_USERNAME and OXYLABS_PASSWORD variables are set
tool = OxylabsAmazonProductScraperTool()
result = tool.run(query="AAAAABBBBCC")
print(result)
```
### Parameters
- `query` - 10-symbol ASIN code.
- `domain` - domain localization for Amazon.
- `geo_location` - the _Deliver to_ location.
- `user_agent_type` - device type and browser.
- `render` - enables JavaScript rendering when set to `html`.
- `callback_url` - URL to your callback endpoint.
- `context` - Additional advanced settings and controls for specialized requirements.
- `parse` - returns parsed data when set to true.
- `parsing_instructions` - define your own parsing and data transformation logic that will be executed on an HTML scraping result.
### Advanced example
```python
from crewai_tools import OxylabsAmazonProductScraperTool
# make sure OXYLABS_USERNAME and OXYLABS_PASSWORD variables are set
tool = OxylabsAmazonProductScraperTool(
config={
"domain": "com",
"parse": True,
"context": [
{
"key": "autoselect_variant",
"value": True
}
]
}
)
result = tool.run(query="AAAAABBBBCC")
print(result)
```
# `OxylabsAmazonSearchScraperTool`
### Example
```python
from crewai_tools import OxylabsAmazonSearchScraperTool
# make sure OXYLABS_USERNAME and OXYLABS_PASSWORD variables are set
tool = OxylabsAmazonSearchScraperTool()
result = tool.run(query="headsets")
print(result)
```
### Parameters
- `query` - Amazon search term.
- `domain` - Domain localization for Bestbuy.
- `start_page` - starting page number.
- `pages` - number of pages to retrieve.
- `geo_location` - the _Deliver to_ location.
- `user_agent_type` - device type and browser.
- `render` - enables JavaScript rendering when set to `html`.
- `callback_url` - URL to your callback endpoint.
- `context` - Additional advanced settings and controls for specialized requirements.
- `parse` - returns parsed data when set to true.
- `parsing_instructions` - define your own parsing and data transformation logic that will be executed on an HTML scraping result.
### Advanced example
```python
from crewai_tools import OxylabsAmazonSearchScraperTool
# make sure OXYLABS_USERNAME and OXYLABS_PASSWORD variables are set
tool = OxylabsAmazonSearchScraperTool(
config={
"domain": 'nl',
"start_page": 2,
"pages": 2,
"parse": True,
"context": [
{'key': 'category_id', 'value': 16391693031}
],
}
)
result = tool.run(query='nirvana tshirt')
print(result)
```
# `OxylabsGoogleSearchScraperTool`
### Example
```python
from crewai_tools import OxylabsGoogleSearchScraperTool
# make sure OXYLABS_USERNAME and OXYLABS_PASSWORD variables are set
tool = OxylabsGoogleSearchScraperTool()
result = tool.run(query="iPhone 16")
print(result)
```
### Parameters
- `query` - search keyword.
- `domain` - domain localization for Google.
- `start_page` - starting page number.
- `pages` - number of pages to retrieve.
- `limit` - number of results to retrieve in each page.
- `locale` - `Accept-Language` header value which changes your Google search page web interface language.
- `geo_location` - the geographical location that the result should be adapted for. Using this parameter correctly is extremely important to get the right data.
- `user_agent_type` - device type and browser.
- `render` - enables JavaScript rendering when set to `html`.
- `callback_url` - URL to your callback endpoint.
- `context` - Additional advanced settings and controls for specialized requirements.
- `parse` - returns parsed data when set to true.
- `parsing_instructions` - define your own parsing and data transformation logic that will be executed on an HTML scraping result.
### Advanced example
```python
from crewai_tools import OxylabsGoogleSearchScraperTool
# make sure OXYLABS_USERNAME and OXYLABS_PASSWORD variables are set
tool = OxylabsGoogleSearchScraperTool(
config={
"parse": True,
"geo_location": "Paris, France",
"user_agent_type": "tablet",
}
)
result = tool.run(query="iPhone 16")
print(result)
```
# `OxylabsUniversalScraperTool`
### Example
```python
from crewai_tools import OxylabsUniversalScraperTool
# make sure OXYLABS_USERNAME and OXYLABS_PASSWORD variables are set
tool = OxylabsUniversalScraperTool()
result = tool.run(url="https://ip.oxylabs.io")
print(result)
```
### Parameters
- `url` - website url to scrape.
- `user_agent_type` - device type and browser.
- `geo_location` - sets the proxy's geolocation to retrieve data.
- `render` - enables JavaScript rendering when set to `html`.
- `callback_url` - URL to your callback endpoint.
- `context` - Additional advanced settings and controls for specialized requirements.
- `parse` - returns parsed data when set to `true`, as long as a dedicated parser exists for the submitted URL's page type.
- `parsing_instructions` - define your own parsing and data transformation logic that will be executed on an HTML scraping result.
### Advanced example
```python
from crewai_tools import OxylabsUniversalScraperTool
# make sure OXYLABS_USERNAME and OXYLABS_PASSWORD variables are set
tool = OxylabsUniversalScraperTool(
config={
"render": "html",
"user_agent_type": "mobile",
"context": [
{"key": "force_headers", "value": True},
{"key": "force_cookies", "value": True},
{
"key": "headers",
"value": {
"Custom-Header-Name": "custom header content",
},
},
{
"key": "cookies",
"value": [
{"key": "NID", "value": "1234567890"},
{"key": "1P JAR", "value": "0987654321"},
],
},
{"key": "http_method", "value": "get"},
{"key": "follow_redirects", "value": True},
{"key": "successful_status_codes", "value": [808, 909]},
],
}
)
result = tool.run(url="https://ip.oxylabs.io")
print(result)
```

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@@ -1,216 +0,0 @@
site_name: crewAI
site_author: crewAI, Inc
site_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.
repo_name: crewAI
repo_url: https://github.com/crewAIInc/crewAI
site_url: https://docs.crewai.com
edit_uri: edit/main/docs/
copyright: Copyright &copy; 2024 crewAI, Inc
markdown_extensions:
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pygments_lang_class: true
- pymdownx.inlinehilite
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repo_url_shorthand: true
user: joaomdmoura
repo: crewAI
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nav:
- Home: '/'
- Getting Started:
- Installing CrewAI: 'getting-started/Installing-CrewAI.md'
- Starting a new CrewAI project: 'getting-started/Start-a-New-CrewAI-Project-Template-Method.md'
- Core Concepts:
- Agents: 'core-concepts/Agents.md'
- Tasks: 'core-concepts/Tasks.md'
- Tools: 'core-concepts/Tools.md'
- Processes: 'core-concepts/Processes.md'
- Crews: 'core-concepts/Crews.md'
- Collaboration: 'core-concepts/Collaboration.md'
- Training: 'core-concepts/Training-Crew.md'
- Memory: 'core-concepts/Memory.md'
- Planning: 'core-concepts/Planning.md'
- Testing: 'core-concepts/Testing.md'
- Using LangChain Tools: 'core-concepts/Using-LangChain-Tools.md'
- Using LlamaIndex Tools: 'core-concepts/Using-LlamaIndex-Tools.md'
- How to Guides:
- Create Custom Tools: 'how-to/Create-Custom-Tools.md'
- Using Sequential Process: 'how-to/Sequential.md'
- Using Hierarchical Process: 'how-to/Hierarchical.md'
- Create your own Manager Agent: 'how-to/Your-Own-Manager-Agent.md'
- Connecting to any LLM: 'how-to/LLM-Connections.md'
- Customizing Agents: 'how-to/Customizing-Agents.md'
- Coding Agents: 'how-to/Coding-Agents.md'
- Forcing Tool Output as Result: 'how-to/Force-Tool-Ouput-as-Result.md'
- Human Input on Execution: 'how-to/Human-Input-on-Execution.md'
- Kickoff a Crew Asynchronously: 'how-to/Kickoff-async.md'
- Kickoff a Crew for a List: 'how-to/Kickoff-for-each.md'
- Replay from a specific task from a kickoff: 'how-to/Replay-tasks-from-latest-Crew-Kickoff.md'
- Conditional Tasks: 'how-to/Conditional-Tasks.md'
- Agent Monitoring with AgentOps: 'how-to/AgentOps-Observability.md'
- Agent Monitoring with LangTrace: 'how-to/Langtrace-Observability.md'
- Agent Monitoring with OpenLIT: 'how-to/openlit-Observability.md'
- Agent Monitoring with MLflow: 'how-to/mlflow-Observability.md'
- Tools Docs:
- Browserbase Web Loader: 'tools/BrowserbaseLoadTool.md'
- Code Docs RAG Search: 'tools/CodeDocsSearchTool.md'
- Code Interpreter: 'tools/CodeInterpreterTool.md'
- Composio Tools: 'tools/ComposioTool.md'
- CSV RAG Search: 'tools/CSVSearchTool.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 Search 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'
- Spider Scraper: 'tools/SpiderTool.md'
- TXT RAG Search: 'tools/TXTSearchTool.md'
- Vision Tool: 'tools/VisionTool.md'
- Website RAG Search: 'tools/WebsiteSearchTool.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"
- Stock Analysis: https://github.com/joaomdmoura/crewAI-examples/tree/main/stock_analysis"
- Game Generator: https://github.com/joaomdmoura/crewAI-examples/tree/main/game-builder-crew"
- Drafting emails with LangGraph: https://github.com/joaomdmoura/crewAI-examples/tree/main/CrewAI-LangGraph"
- Landing Page Generator: https://github.com/joaomdmoura/crewAI-examples/tree/main/landing_page_generator"
- Prepare for meetings: https://github.com/joaomdmoura/crewAI-examples/tree/main/prep-for-a-meeting"
- Telemetry: 'telemetry/Telemetry.md'
- Change Log: 'https://github.com/crewAIInc/crewAI/releases'
extra_css:
- stylesheets/output.css
- stylesheets/extra.css
plugins:
- social
- search
extra:
analytics:
provider: google
property: G-N3Q505TMQ6
social:
- icon: fontawesome/brands/x-twitter
link: https://x.com/crewAIInc
- icon: fontawesome/brands/github
link: https://github.com/crewAIInc/crewAI

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@@ -74,11 +74,6 @@ dev-dependencies = [
"ruff>=0.8.2",
"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",
"pytest>=8.0.0",

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@@ -39,7 +39,7 @@ from crewai.tasks.output_format import OutputFormat
from crewai.tasks.task_output import TaskOutput
from crewai.tools.base_tool import BaseTool
from crewai.utilities.config import process_config
from crewai.utilities.constants import NOT_SPECIFIED
from crewai.utilities.constants import NOT_SPECIFIED, _NotSpecified
from crewai.utilities.guardrail import process_guardrail, GuardrailResult
from crewai.utilities.converter import Converter, convert_to_model
from crewai.utilities.events import (
@@ -95,9 +95,9 @@ class Task(BaseModel):
agent: Optional[BaseAgent] = Field(
description="Agent responsible for execution the task.", default=None
)
context: Optional[List["Task"]] = Field(
context: Union[List["Task"], None, _NotSpecified] = Field(
description="Other tasks that will have their output used as context for this task.",
default=NOT_SPECIFIED,
default=NOT_SPECIFIED
)
async_execution: Optional[bool] = Field(
description="Whether the task should be executed asynchronously or not.",
@@ -158,6 +158,9 @@ class Task(BaseModel):
end_time: Optional[datetime.datetime] = Field(
default=None, description="End time of the task execution"
)
model_config = {
"arbitrary_types_allowed": True
}
@field_validator("guardrail")
@classmethod

View File

@@ -476,7 +476,14 @@ def load_agent_from_repository(from_repository: str) -> Dict[str, Any]:
try:
module = importlib.import_module(tool["module"])
tool_class = getattr(module, tool["name"])
attributes[key].append(tool_class())
tool_value = tool_class(**tool["init_params"])
if isinstance(tool_value, list):
attributes[key].extend(tool_value)
else:
attributes[key].append(tool_value)
except Exception as e:
raise AgentRepositoryError(
f"Tool {tool['name']} could not be loaded: {e}"

View File

@@ -1,5 +1,5 @@
from typing import TYPE_CHECKING, List
from typing import TYPE_CHECKING, List, Union
from crewai.utilities.constants import _NotSpecified
if TYPE_CHECKING:
from crewai.task import Task
@@ -15,7 +15,7 @@ def aggregate_raw_outputs_from_task_outputs(task_outputs: List["TaskOutput"]) ->
return context
def aggregate_raw_outputs_from_tasks(tasks: List["Task"]) -> str:
def aggregate_raw_outputs_from_tasks(tasks: Union[List["Task"],_NotSpecified]) -> str:
"""Generate string context from the tasks."""
task_outputs = (

View File

@@ -2099,7 +2099,7 @@ def mock_get_auth_token():
@patch("crewai.cli.plus_api.PlusAPI.get_agent")
def test_agent_from_repository(mock_get_agent, mock_get_auth_token):
from crewai_tools import SerperDevTool, XMLSearchTool
from crewai_tools import SerperDevTool, XMLSearchTool, CSVSearchTool, EnterpriseActionTool
mock_get_response = MagicMock()
mock_get_response.status_code = 200
@@ -2108,19 +2108,42 @@ def test_agent_from_repository(mock_get_agent, mock_get_auth_token):
"goal": "test goal",
"backstory": "test backstory",
"tools": [
{"module": "crewai_tools", "name": "SerperDevTool"},
{"module": "crewai_tools", "name": "XMLSearchTool"},
{"module": "crewai_tools", "name": "SerperDevTool", "init_params": {"n_results": 30}},
{"module": "crewai_tools", "name": "XMLSearchTool", "init_params": {"summarize": True}},
{"module": "crewai_tools", "name": "CSVSearchTool", "init_params": {}},
# using a tools that returns a list of BaseTools
{"module": "crewai_tools", "name": "CrewaiEnterpriseTools", "init_params": {"actions_list": [], "enterprise_token": "test_key"}},
],
}
mock_get_agent.return_value = mock_get_response
agent = Agent(from_repository="test_agent")
tool_action = EnterpriseActionTool(
name="test_name",
description="test_description",
enterprise_action_token="test_token",
action_name="test_action_name",
action_schema={"test": "test"},
)
with patch("crewai_tools.CrewaiEnterpriseTools", return_value=[tool_action]):
agent = Agent(from_repository="test_agent")
assert agent.role == "test role"
assert agent.goal == "test goal"
assert agent.backstory == "test backstory"
assert len(agent.tools) == 2
assert len(agent.tools) == 4
assert isinstance(agent.tools[0], SerperDevTool)
assert agent.tools[0].n_results == 30
assert isinstance(agent.tools[1], XMLSearchTool)
assert agent.tools[1].summarize
assert isinstance(agent.tools[2], CSVSearchTool)
assert not agent.tools[2].summarize
assert isinstance(agent.tools[3], EnterpriseActionTool)
assert agent.tools[3].name == "test_name"
@patch("crewai.cli.plus_api.PlusAPI.get_agent")
@@ -2133,7 +2156,7 @@ def test_agent_from_repository_override_attributes(mock_get_agent, mock_get_auth
"role": "test role",
"goal": "test goal",
"backstory": "test backstory",
"tools": [{"name": "SerperDevTool", "module": "crewai_tools"}],
"tools": [{"name": "SerperDevTool", "module": "crewai_tools", "init_params": {}}],
}
mock_get_agent.return_value = mock_get_response
agent = Agent(from_repository="test_agent", role="Custom Role")

View File

@@ -0,0 +1,43 @@
from pathlib import Path
from crewai.cli.constants import PROVIDERS
def test_cli_documentation_matches_providers():
"""Test that CLI documentation accurately reflects the available providers."""
docs_path = Path(__file__).parent.parent / "docs" / "concepts" / "cli.mdx"
with open(docs_path, 'r') as f:
docs_content = f.read()
assert "top 5" not in docs_content.lower(), "Documentation should not mention 'top 5' providers"
assert "5 most common" not in docs_content.lower(), "Documentation should not mention '5 most common' providers"
assert "list of available LLM providers" in docs_content or "following LLM providers" in docs_content, \
"Documentation should mention the availability of multiple LLM providers"
assert len(PROVIDERS) > 5, f"Expected more than 5 providers, but found {len(PROVIDERS)}"
key_providers = ["OpenAI", "Anthropic", "Gemini"]
for provider in key_providers:
assert provider in docs_content, f"Key provider {provider} should be mentioned in documentation"
def test_providers_list_matches_constants():
"""Test that the actual PROVIDERS list has the expected providers."""
expected_providers = [
"openai",
"anthropic",
"gemini",
"nvidia_nim",
"groq",
"huggingface",
"ollama",
"watson",
"bedrock",
"azure",
"cerebras",
"sambanova",
]
assert PROVIDERS == expected_providers, f"PROVIDERS list has changed. Expected {expected_providers}, got {PROVIDERS}"
assert len(PROVIDERS) == 12, f"Expected 12 providers, but found {len(PROVIDERS)}"

252
uv.lock generated
View File

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@@ -787,11 +778,6 @@ tools = [
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{ name = "mkdocs" },
{ name = "mkdocs-material" },
{ name = "mkdocs-material-extensions" },
{ name = "mkdocstrings" },
{ name = "mkdocstrings-python" },
{ name = "mypy" },
{ name = "pillow" },
{ name = "pre-commit" },
@@ -846,11 +832,6 @@ requires-dist = [
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{ name = "mkdocs", specifier = ">=1.4.3" },
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{ name = "pillow", specifier = ">=10.2.0" },
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