83 lines
3.2 KiB
Python
83 lines
3.2 KiB
Python
"""Transient-transport retry count + per-model client-cache isolation.
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Two related hardening behaviors for auxiliary calls (which include MoA
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reference advisors, a pinned-model path where provider fallback is not a
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meaningful recovery):
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1. A transient transport blip (connection reset / timeout / 5xx) is retried
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on the SAME provider several times with backoff before giving up — a single
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upstream blip should not silently lose a pinned auxiliary call (root of the
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run2 double-advisor "Connection error" collapse).
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2. Two auxiliary calls to the same provider/base_url/key but DIFFERENT models
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get DISTINCT client-cache keys, so a concurrent fan-out (e.g. opus + gpt-5.5
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advisors) never shares one client entry.
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"""
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from __future__ import annotations
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import os
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import types
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from unittest.mock import patch
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import pytest
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class _ConnErr(Exception):
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"""Stand-in that the transient detector recognizes as a connection blip."""
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def test_transient_retry_count_default(monkeypatch):
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from agent import auxiliary_client as ac
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# No config value -> default.
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monkeypatch.setattr(ac, "load_config", lambda: {}, raising=False)
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with patch("hermes_cli.config.load_config", return_value={}), \
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patch("hermes_cli.config.cfg_get", return_value=None):
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assert ac._transient_retry_count() == ac._DEFAULT_TRANSIENT_RETRIES
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def test_transient_retry_count_configurable_and_clamped():
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from agent import auxiliary_client as ac
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with patch("hermes_cli.config.cfg_get", return_value=4):
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assert ac._transient_retry_count() == 4
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with patch("hermes_cli.config.cfg_get", return_value=100):
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assert ac._transient_retry_count() == 6 # clamped high
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with patch("hermes_cli.config.cfg_get", return_value=-3):
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assert ac._transient_retry_count() == 0 # clamped low
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with patch("hermes_cli.config.cfg_get", side_effect=RuntimeError):
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assert ac._transient_retry_count() == ac._DEFAULT_TRANSIENT_RETRIES
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def test_model_participates_in_client_cache_key():
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"""Same provider/base_url/key, different model -> different cache key.
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This is what stops two concurrent advisors from sharing (and racing on)
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one cached client entry."""
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from agent.auxiliary_client import _client_cache_key
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k_opus = _client_cache_key(
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"openrouter", async_mode=False, base_url="https://openrouter.ai/api/v1",
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api_key="K", model="anthropic/claude-opus-4.8",
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)
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k_gpt = _client_cache_key(
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"openrouter", async_mode=False, base_url="https://openrouter.ai/api/v1",
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api_key="K", model="openai/gpt-5.5",
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)
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assert k_opus != k_gpt
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# Same model still collides (cache still works for reuse).
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k_opus2 = _client_cache_key(
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"openrouter", async_mode=False, base_url="https://openrouter.ai/api/v1",
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api_key="K", model="anthropic/claude-opus-4.8",
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)
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assert k_opus == k_opus2
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def test_missing_model_key_is_stable():
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"""Omitting model (legacy callers) is still a valid, stable key."""
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from agent.auxiliary_client import _client_cache_key
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a = _client_cache_key("openrouter", async_mode=False, base_url="u", api_key="k")
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b = _client_cache_key("openrouter", async_mode=False, base_url="u", api_key="k")
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assert a == b
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