Private flows

Create isolated execution environments within your workflows.

Nested flows in ControlFlow allow you to create isolated threads within a larger workflow. This feature is particularly useful when you need to perform operations that shouldn’t affect or be visible to the main flow, or when you want to encapsulate a set of tasks for modularity or security reasons.

In this example, we’ll demonstrate how to use private flows to process sensitive information without exposing it to the main workflow. In a real-world version of this, you might use a locally-hosted LLM or private API for the sensitive data processing.

Code

Code

import controlflow as cf

@cf.flow(args_as_context=False)
def process_user_data(user_name: str, sensitive_info: str):
    # Main flow context
    print(f"Processing data for user: {user_name}")

    # Create a private flow to handle sensitive information
    with cf.Flow() as private_flow:
        # This task runs in an isolated context
        masked_info = cf.run(
            "Mask the sensitive information",
            context={"sensitive_info": sensitive_info},
            result_type=str
        )
    
    # Task in the main flow can be provided the masked_info as context
    summary = cf.run(
        "Summarize the data processing result",
        context={"user_name": user_name, "masked_info": masked_info},
        result_type=str
    )

    return summary

# Execute the flow
result = process_user_data("Alice", "SSN: 123-45-6789")
print(result)

Key points

1. Isolation: Private flows create an isolated execution environment. Tasks within a private flow cannot access or modify the context of the parent flow directly.

2. Data encapsulation: Sensitive information (sensitive_info) is only available within the private flow, protecting it from accidental exposure in the main workflow.

3. Context control: By setting args_as_context=False, we can pass the sensitive information to the flow function without adding it to context automatically.

4. Result passing: Results from the private flow (like masked_info) can be explicitly passed back to the main flow for further processing.

5. Nested structure: Private flows can be nested within larger workflows, allowing for modular and secure task organization.

Further reading

• To learn more about flows in ControlFlow, see the flows documentation.

By using private flows, you can create more secure and modular workflows, especially when dealing with sensitive information or when you need to isolate certain operations from the main workflow context.