Continue-As-New

Continue-As-New resets the workflow's event history while carrying forward its state, enabling indefinitely long-running workflows without hitting history size limits.

• Long-running workflows that iterate indefinitely
• When workflow history approaches size limits (~50K events or 50MB)
• Workflows that need to run for weeks or months

When continue_as_new() is called, the current run completes and a new run starts fresh from the beginning with the provided state. The event history is reset, while the state you pass to continue_as_new() is carried forward.

Important: Your workflow's run method must accept the carry-forward state as parameters to restore its state when continuing as new.

Use workflows.workflow.should_continue_as_new() to check whether the current run is approaching the history limit; it returns True when the event history is close to the cap.

import mistralai.workflows as workflows
from pydantic import BaseModel

class ProcessorState(BaseModel):
    page: int = 0
    total_processed: int = 0

@workflows.workflow.define(name="long-running-processor")
class LongRunningProcessor:
    @workflows.workflow.entrypoint
    async def run(self, page: int = 0, total_processed: int = 0):  # State parameters are required
        while True:
            # Process current page
            result = await process_page(page)
            total_processed += result.count
            page += 1

            # When history grows large, restart with a fresh history
            if workflows.workflow.should_continue_as_new():
                workflows.workflow.continue_as_new(ProcessorState(page=page, total_processed=total_processed))

import mistralai.workflows as workflows
from pydantic import BaseModel

class ProcessorState(BaseModel):
    page: int = 0
    total_processed: int = 0

@workflows.workflow.define(name="long-running-processor")
class LongRunningProcessor:
    @workflows.workflow.entrypoint
    async def run(self, page: int = 0, total_processed: int = 0):  # State parameters are required
        while True:
            # Process current page
            result = await process_page(page)
            total_processed += result.count
            page += 1

            # When history grows large, restart with a fresh history
            if workflows.workflow.should_continue_as_new():
                workflows.workflow.continue_as_new(ProcessorState(page=page, total_processed=total_processed))

For the related concept on the canonical Workflows page, see Building Workflows > Workflows > Continue-as-new and Core Concepts > Workflows > Determinism.