forked from Zakaria/hermes-agent
Hermes-agent
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"""Retry utilities — jittered backoff for decorrelated retries.
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Replaces fixed exponential backoff with jittered delays to prevent
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thundering-herd retry spikes when multiple sessions hit the same
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rate-limited provider concurrently.
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"""
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import random
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import threading
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import time
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# Monotonic counter for jitter seed uniqueness within the same process.
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# Protected by a lock to avoid race conditions in concurrent retry paths
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# (e.g. multiple gateway sessions retrying simultaneously).
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_jitter_counter = 0
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_jitter_lock = threading.Lock()
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def jittered_backoff(
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attempt: int,
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*,
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base_delay: float = 5.0,
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max_delay: float = 120.0,
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jitter_ratio: float = 0.5,
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) -> float:
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"""Compute a jittered exponential backoff delay.
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Args:
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attempt: 1-based retry attempt number.
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base_delay: Base delay in seconds for attempt 1.
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max_delay: Maximum delay cap in seconds.
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jitter_ratio: Fraction of computed delay to use as random jitter
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range. 0.5 means jitter is uniform in [0, 0.5 * delay].
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Returns:
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Delay in seconds: min(base * 2^(attempt-1), max_delay) + jitter.
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The jitter decorrelates concurrent retries so multiple sessions
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hitting the same provider don't all retry at the same instant.
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"""
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global _jitter_counter
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with _jitter_lock:
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_jitter_counter += 1
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tick = _jitter_counter
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exponent = max(0, attempt - 1)
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if exponent >= 63 or base_delay <= 0:
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delay = max_delay
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else:
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delay = min(base_delay * (2 ** exponent), max_delay)
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# Seed from time + counter for decorrelation even with coarse clocks.
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seed = (time.time_ns() ^ (tick * 0x9E3779B9)) & 0xFFFFFFFF
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rng = random.Random(seed)
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jitter = rng.uniform(0, jitter_ratio * delay)
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return delay + jitter
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