Concurrency

# BAD — concurrent requests overwrite each other
results = {}

def process(text):
    results["output"] = expensive_compute(text)  # race condition
    return results["output"]

# GOOD — pure function, no shared mutable state
def process(text):
    return expensive_compute(text)

with gr.Blocks() as demo:
    history = gr.State(value=[])

    def add_message(msg, hist):
        hist.append(msg)
        return hist, hist

    btn.click(fn=add_message, inputs=[msg, history], outputs=[chatbot, history])

# BAD — concurrent calls clobber the same file
def generate_image(prompt):
    image = pipe(prompt).images[0]
    image.save("output.png")
    return "output.png"

# GOOD — unique path per invocation
import tempfile

def generate_image(prompt):
    image = pipe(prompt).images[0]
    with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as f:
        image.save(f.name)
        return f.name

# SAFE — loaded once at module scope, read-only during requests
model = load_model().to("cuda")
tokenizer = load_tokenizer()

@spaces.GPU
def predict(text):
    tokens = tokenizer(text, return_tensors="pt").to("cuda")
    return model.generate(**tokens)