Welcome to Swarms Tools, the ultimate package for integrating cutting-edge APIs into Python functions with seamless multi-agent system compatibility. Designed for enterprises at the forefront of innovation, Swarms Tools is your key to simplifying complexity and unlocking operational excellence.
- Unified API Integration: Ready-to-use Python functions for financial data, social media, IoT, and more.
- Enterprise-Grade Design: Comprehensive type hints, structured outputs, and robust documentation.
- Agent-Ready Framework: Optimized for seamless integration into Swarms' multi-agent orchestration systems.
- Expandable Architecture: Easily extend functionality with a standardized schema for new tools.
pip3 install -U swarms-tools
swarms-tools/
├── swarms_tools/
│ ├── financial_data/
│ │ ├── htx_tool.py
│ │ ├── eodh_api.py
│ │ └── coingecko_tool.py
│ ├── social_media/
│ │ ├── telegram_tool.py
│ ├── utilities/
│ │ └── logging.py
├── tests/
│ ├── test_financial_data.py
│ └── test_social_media.py
└── README.md
Enable precise and actionable financial insights:
from swarms_tools.financial_data.htx_tool import fetch_htx_data
# Fetch historical trading data for "Swarms Corporation"
response = fetch_htx_data("swarms")
print(response)
from swarms_tools.financial_data.eodh_api import fetch_stock_news
# Retrieve latest stock news for Apple
news = fetch_stock_news("AAPL")
print(news)
from swarms_tools.financial_data.coingecko_tool import coin_gecko_coin_api
# Fetch live data for Bitcoin
crypto_data = coin_gecko_coin_api("bitcoin")
print(crypto_data)
Streamline communication and engagement:
from swarms_tools.social_media.telegram_tool import telegram_dm_or_tag_api
def send_alert(response: str):
telegram_dm_or_tag_api(response)
# Send a message to a user or group
send_alert("Mission-critical update from Swarms.")
Every tool in Swarms Tools adheres to a strict schema for maintainability and interoperability:
-
Functionality:
- Encapsulate API logic into a modular, reusable function.
-
Typing:
- Leverage Python type hints for input validation and clarity.
Example:
def fetch_data(symbol: str, date_range: str) -> str: """ Fetch financial data for a given symbol and date range. Args: symbol (str): Ticker symbol of the asset. date_range (str): Timeframe for the data (e.g., '1d', '1m', '1y'). Returns: dict: A dictionary containing financial metrics. """ pass
-
Documentation:
- Include detailed docstrings with parameter explanations and usage examples.
-
Output Standardization:
- Ensure consistent outputs (e.g., strings) for easy downstream agent integration.
-
API-Key Management:
- All API keys must be fetched with
os.getenv("YOUR_KEY")
- All API keys must be fetched with
Comprehensive documentation is available to guide developers and enterprises. Visit our official docs for detailed API references, usage examples, and best practices.
We welcome contributions from the global developer community. To contribute:
- Fork the Repository: Start by forking the repository.
- Create a Feature Branch: Use a descriptive branch name:
feature/add-new-tool
. - Commit Your Changes: Write meaningful commit messages.
- Submit a Pull Request: Open a pull request for review.
This project is licensed under the MIT License. See the LICENSE file for details.
Explore the limitless possibilities of agent-based systems. Together, we can build a smarter, faster, and more interconnected world.
Visit us: Swarms Corporation
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"The future belongs to those who dare to automate it."
— The Swarms Corporation