Timeouts

from tensorlake.applications import function

@function(timeout=1800)  # 30 minutes
def deep_research(prompt: str) -> str:
    ...

from tensorlake.applications import function, RequestContext

@function(timeout=300)  # 5 minute timeout
def long_running_task(items: list) -> dict:
    ctx = RequestContext.get()

    # After 3 minutes of processing...
    ctx.progress.update(50, 100, "Halfway done")

    # Timeout just reset to 5 minutes from NOW
    # Function can run another 5 minutes before next update

    # Continue processing...

@function(timeout=300)  # 5 minute timeout per iteration
def persistent_agent(task: str) -> str:
    ctx = RequestContext.get()

    for iteration in range(1000):
        ctx.progress.update(iteration, 1000)  # resets timeout
        result = agent_iteration(task)
        if is_complete(result):
            return result

@function(timeout=600)  # 10 minute timeout
def process_stream(stream_url: str) -> dict:
    ctx = RequestContext.get()
    count = 0

    for item in stream_items(stream_url):
        ctx.progress.update(count, count + 1, f"Processed {count} items")
        process(item)
        count += 1

    return {"total": count}

@function(timeout=300)
def process_video(video_url: str) -> str:
    ctx = RequestContext.get()

    frames = extract_frames(video_url)
    total_frames = len(frames)

    for i, frame in enumerate(frames):
        if i % 100 == 0:
            ctx.progress.update(i, total_frames, f"Processing frame {i}/{total_frames}")
        process_frame(frame)

    return "complete"