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    Home»Machine Learning»A Step-by-Step Guide to LLM Function Calling in Python | by angu sundaresh | Feb, 2025
    Machine Learning

    A Step-by-Step Guide to LLM Function Calling in Python | by angu sundaresh | Feb, 2025

    FinanceStarGateBy FinanceStarGateFebruary 12, 2025No Comments1 Min Read
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    Perform calling permits Claude to work together with exterior features and instruments in a structured method. This information will stroll you thru implementing perform calling with Claude utilizing Python, full with examples and greatest practices.

    Stipulations

    To get began, you’ll want:

    • Python 3.7+
    • anthropic Python bundle
    • A legitimate API key from Anthropic

    Fundamental Setup

    from anthropic import Anthropic
    import json
    # Initialize the consumer
    anthropic = Anthropic(api_key='your-api-key')

    Defining Capabilities

    function_schema = {
    "identify": "get_weather",
    "description": "Get the present climate for a particular location",
    "parameters": {
    "sort": "object",
    "properties": {
    "location": {
    "sort": "string",
    "description": "Metropolis identify or coordinates"
    },
    "unit": {
    "sort": "string",
    "enum": ["celsius", "fahrenheit"],
    "description": "Temperature unit"
    }
    },
    "required": ["location"]
    }
    }

    Making Perform Calls

    def get_weather(location, unit="celsius"):
    # It is a mock implementation however you possibly can all name your API
    return {
    "location": location,
    "temperature": 22 if unit ==…



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