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Tasks can be equipped with various tools to extend their capabilities. Tools are added through the tools parameter and can include custom functions, built-in tools, or tool collections.

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Single Tool

from upsonic.tools import tool

@tool
def web_search(query: str) -> str:
    """Search the web for information."""
    return f"Search results for: {query}"

task = Task(
    description="Search for information about AI",
    tools=[web_search]
)

​
Multiple Tools

from upsonic.tools import tool

@tool
def web_search(query: str) -> str:
    """Search the web for information."""
    return f"Search results for: {query}"

@tool
def data_processor(data: str) -> str:
    """Process and analyze data."""
    return f"Processed: {data}"

# Task with multiple tools
task = Task(
    description="Search for information about AI and process the results",
    tools=[web_search, data_processor]
)

​
Tool Collections

from upsonic.tools import YFinanceTools

# Create a tool collection
finance_tools = YFinanceTools(
    stock_price=True,
    company_info=True,
    analyst_recommendations=True
)

# Task with tool collection
task = Task(
    description="Get stock information for AAPL",
    tools=finance_tools.functions()
)

​
Tool Configuration

from upsonic.tools import tool

@tool(requires_confirmation=True, cache_results=True)
def sensitive_operation(data: str) -> str:
    """Perform a sensitive operation that requires confirmation."""
    return f"Processed sensitive data: {data}"

task = Task(
    description="Process sensitive information",
    tools=[sensitive_operation]
)

​
Available Tool Configurations

ConfigurationTypeDescription
requires_confirmationboolPause for user confirmation before execution
requires_user_inputboolPrompt user for input during execution
user_input_fieldsList[str]Fields to prompt user for when requires_user_input is True
external_executionboolHandle execution externally (advanced use-cases)
show_resultboolDisplay result directly to user without LLM processing
stop_after_tool_callboolTerminate agent after this tool call

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Best Practices

  • Tool Validation: All tools must have type hints and docstrings
  • Single Responsibility: Each tool should have a clear, focused purpose
  • Error Handling: Implement proper error handling within tool functions
  • Configuration: Use tool configurations appropriately for security and user experience
  • Documentation: Write clear docstrings that explain the tool’s purpose to the LLM
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