Swarms Tools¶

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.

🚀 Features¶

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.

🔧 Installation¶

pip3 install -U swarms-tools

📂 Directory Structure¶

swarms-tools/
├── swarms_tools/
│   ├── finance/
│   │   ├── 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

💼 Use Cases¶

Finance¶

Explore our diverse range of financial tools, designed to streamline your operations. If you need a tool not listed, feel free to submit an issue or accelerate integration by contributing a pull request with your tool of choice.

Tool Name	Function	Description
`fetch_stock_news`	`fetch_stock_news`	Fetches the latest stock news and updates.
`fetch_htx_data`	`fetch_htx_data`	Retrieves financial data from the HTX platform.
`yahoo_finance_api`	`yahoo_finance_api`	Fetches comprehensive stock data from Yahoo Finance, including prices and trends.
`coin_gecko_coin_api`	`coin_gecko_coin_api`	Fetches cryptocurrency data from CoinGecko, including market and price information.
`helius_api_tool`	`helius_api_tool`	Retrieves blockchain account, transaction, or token data using the Helius API.
`okx_api_tool`	`okx_api_tool`	Fetches detailed cryptocurrency data for coins from the OKX exchange.

Financial Data Retrieval¶

Enable precise and actionable financial insights:

Example 1: Fetch Historical Data¶

from swarms_tools import fetch_htx_data

# Fetch historical trading data for "Swarms Corporation"
response = fetch_htx_data("swarms")
print(response)

Example 2: Stock News Analysis¶

from swarms_tools import fetch_stock_news

# Retrieve latest stock news for Apple
news = fetch_stock_news("AAPL")
print(news)

Example 3: Cryptocurrency Metrics¶

from swarms_tools import coin_gecko_coin_api

# Fetch live data for Bitcoin
crypto_data = coin_gecko_coin_api("bitcoin")
print(crypto_data)

Streamline communication and engagement:

Example: Telegram Bot Messaging¶

from swarms_tools 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.")

Dex Screener¶

This is a tool that allows you to fetch data from the Dex Screener API. It supports multiple chains and multiple tokens.

from swarms_tools.finance.dex_screener import (
    fetch_latest_token_boosts,
    fetch_dex_screener_profiles,
)


fetch_dex_screener_profiles()
fetch_latest_token_boosts()

Structs¶

The tool chainer enables the execution of multiple tools in a sequence, allowing for the aggregation of their results in either a parallel or sequential manner.

# Example usage
from loguru import logger

from swarms_tools.structs import tool_chainer


if __name__ == "__main__":
    logger.add("tool_chainer.log", rotation="500 MB", level="INFO")

    # Example tools
    def tool1():
        return "Tool1 Result"

    def tool2():
        return "Tool2 Result"

    # def tool3():
    #     raise ValueError("Simulated error in Tool3")

    tools = [tool1, tool2]

    # Parallel execution
    parallel_results = tool_chainer(tools, parallel=True)
    print("Parallel Results:", parallel_results)

    # Sequential execution
    # sequential_results = tool_chainer(tools, parallel=False)
    # print("Sequential Results:", sequential_results)

¶

🧩 Standardized Schema¶

Every tool in Swarms Tools adheres to a strict schema for maintainability and interoperability:

Schema Template¶

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")

📖 Documentation¶

Comprehensive documentation is available to guide developers and enterprises. Visit our official docs for detailed API references, usage examples, and best practices.

🛠 Contributing¶

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.

🛡️ License¶

This project is licensed under the MIT License. See the LICENSE file for details.

🌠 Join the Future¶

Explore the limitless possibilities of agent-based systems. Together, we can build a smarter, faster, and more interconnected world.

Visit us: Swarms Corporation
Follow us: Twitter

"The future belongs to those who dare to automate it."
— The Swarms Corporation