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Tool Calling

LLMfy supports tool calling across all providers. Define Python functions with the @Tool() decorator and register them with the agent — LLMfy handles the tool-calling loop automatically.

Define Tools

Decorate any callable function with @Tool():

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from llmfy import Tool

@Tool()
def get_current_weather(location: str, unit: str = "celsius") -> str:
    return f"The weather in {location} is 22 degrees {unit}"

@Tool()
def get_current_time(location: str) -> str:
    return f"The time in {location} is 09:00 AM"

tools = [get_current_weather, get_current_time]

The decorator reads the function signature and docstring to build the schema passed to the model. For best results, add a Google-style docstring describing each parameter.

Provider Support

Tool calling works identically across all providers — only the model initialization differs:

OpenAI

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from llmfy import OpenAIModel, OpenAIConfig

llm = OpenAIModel(model="gpt-4o-mini", config=OpenAIConfig(temperature=0.7))

AWS Bedrock

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from llmfy import BedrockModel, BedrockConfig

llm = BedrockModel(model="amazon.nova-lite-v1:0", config=BedrockConfig(temperature=0.7))

Google AI

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from llmfy import GoogleAIModel, GoogleAIConfig

llm = GoogleAIModel(model="gemini-2.5-flash-lite", config=GoogleAIConfig(temperature=0.7))

Register Tools

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from llmfy import LLMfy

agent = LLMfy(llm, system_message="You are a helpful assistant.")
agent.register_tool(tools)

Using Chat With Tools

chat_with_tools accepts a Message list and runs the tool-calling loop until the model returns a final text response:

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from llmfy import Message, Role

messages = [
    Message(
        role=Role.USER,
        content="What is the time and weather in London?",
    )
]

response = agent.chat_with_tools(messages)
print(f"\n>> {response.result.content}\n")

Output: 

>> The weather in London is 22 degrees celsius and the time is 09:00 AM.

Using Invoke With Tools

invoke_with_tools accepts plain text or a Content list instead of messages:

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response = agent.invoke_with_tools("What is the time and weather in London?")
print(f"\n>> {response.result.content}\n")