Route Tool Call Name to Python Handler Dict

Routes a tool call name to the correct Python handler function using a dictionary lookup, returning an error for unknown tools.

Easy Python 3.9+ Aug 9, 2026 AI & LLM integration patterns 12 views 0 copies

tool-calls llm-integration dictionary-mapping routing

Python code

29 lines

Python 3.9+

def get_name():
    return {"name": "Alice"}

def get_age():
    return {"age": 30}

def get_email():
    return {"email": "alice@example.com"}

handlers = {
    "get_name": get_name,
    "get_age": get_age,
    "get_email": get_email,
}

def route(tool_call):
    handler = handlers.get(tool_call["name"])
    if handler is None:
        return {"error": f"Unknown tool: {tool_call['name']}"}
    return handler()

if __name__ == "__main__":
    tool_calls = [
        {"name": "get_name"},
        {"name": "get_email"},
        {"name": "unknown_tool"},
    ]
    for call in tool_calls:
        print(f"{call['name']}: {route(call)}")

Output

stdout

get_name: {'name': 'Alice'}
get_email: {'email': 'alice@example.com'}
unknown_tool: {'error': "Unknown tool: unknown_tool"}

How it works

This pattern maps AI tool-call names to Python functions using a dictionary. The get method safely returns None when the key is missing, letting us return a helpful error. Each handler is a callable that receives no arguments here, but you can extend handlers to accept parameters from the tool call. This approach is central to building reliable agentic workflows where LLM requests trigger specific backend operations.

Common mistakes

Forgetting to include the `if __name__ == '__main__':` guard in production scripts.
Assuming every tool name exists without using `.get()` and returning a fallback.
Passing extra arguments to handlers that don't accept them.

Variations

Use `functools.partial` to pre-bind arguments for handlers that need parameters.
Use a `match` statement with `case` blocks if you prefer explicit branching over a dict.

Real-world use cases

Routing LLM-generated function calls to backend services in a chatbot.
Mapping API endpoint names to serverless handlers in a microservice gateway.
Dispatching user commands to plugin functions in a CLI application.

Route Tool Call Name to Python Handler Dict

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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