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perf(agent-loop): cut 47% of per-conversation function calls via 3 targeted hot-path optimizations (#28866)
* perf(config): add load_config_readonly() fast path for hot agent loop
`load_config()` is called from the agent loop's per-API-call hot path via
`get_provider_request_timeout()` and `get_provider_stale_timeout()` —
both invoked once per turn from `_resolved_api_call_timeout()` in
run_agent.py.
Profiling a synthetic 20-tool-call agent run revealed:
- 21 invocations of `load_config()` cumulating 56ms (~17% of agent loop)
- 34,398 deepcopy calls totaling 37ms (config defensive deepcopy + chain)
- 8,652 `_expand_env_vars` invocations (~412 per turn)
Microbench (cache-hit, real config.yaml present):
load_config() 265us/call (125us deepcopy + 140us infra)
load_config_readonly() 138us/call (~48% faster)
`load_config_readonly()` returns the cached dict directly without the
defensive deepcopy. Documented contract: caller must not mutate. Returns
plain dict (not MappingProxyType) so downstream `isinstance(x, dict)`
guards keep working — caught during initial implementation when
MappingProxyType broke get_provider_request_timeout's guard logic.
Wired into hermes_cli/timeouts.py (the two functions called per agent
turn). load_config() is unchanged for the 263 other call sites that
mutate the result before save_config(), are not in the hot path, or
where the safety guarantee matters more than the perf.
Profile A/B (cached config, 21-turn agent loop):
BEFORE AFTER delta
get_provider_request_timeout 55ms 16ms -71%
total function calls 399k 160k -60%
deepcopy calls (in hotspots) 34,398 ~0 ~elim
Verified:
- isinstance(load_config_readonly(), dict) is True
- timeout/stale resolutions correct
- load_config() still returns isolated mutable deepcopies
- tests/hermes_cli/test_config*.py / test_timeouts.py: 102/102 pass
- tests/cli/ + tests/agent/test_auxiliary_client.py: 883/883 pass
* perf(redact): substring pre-screens skip non-matching regex chains
Every log record passes through `RedactingFormatter.format` which calls
`redact_sensitive_text`, which historically ran ALL 13 secret-pattern
regexes against every line — including DB connection strings, JWTs,
Discord mentions, Signal phone numbers, etc. — even for typical clean
log records like 'INFO run_agent: API call completed'.
Add cheap substring pre-checks before each regex pass. False positives
still run the regex (which then matches nothing); false negatives are
impossible because every pattern requires the gated substring to match
its leading anchor:
- `_PREFIX_RE` gated on any of 33 known credential prefix substrings
- `_ENV_ASSIGN_RE` gated on `=` in text
- `_JSON_FIELD_RE` gated on `:` and `"` in text
- `_AUTH_HEADER_RE` gated on `uthorization`/`UTHORIZATION` in text
- `_TELEGRAM_RE` gated on `:` in text
- `_PRIVATE_KEY_RE` gated on `BEGIN` and `-----`
- `_DB_CONNSTR_RE` gated on `://` in text
- `_JWT_RE` gated on `eyJ` in text
- URL userinfo/query gated on `://`
- `_redact_form_body` gated on `&` and `=`
- `_DISCORD_MENTION_RE` gated on `<@`
- `_SIGNAL_PHONE_RE` gated on `+`
Microbench (5 typical log records, 20k iterations each):
BEFORE AFTER delta
redact_sensitive_text per call 5.63us 1.79us -68%
Real-world impact: ~244 log records emitted in a 30-turn agent loop, so
the chain saves ~1ms of CPU per conversation. Bigger win is the
reduction in regex execution and GC pressure during heavy logging
sessions (verbose logging, gateway message processing).
Security regression test: 30 secret-containing inputs (sk-/ghp_/JWT/DB
connstr/Auth-Bearer/private key/URL userinfo/Discord/Signal/etc.)
verified to produce identical redacted output before/after. All 75
existing tests/agent/test_redact.py cases pass.
The `?access_token=foo&code=bar` (bare query string, no scheme) case
that 'leaks' is pre-existing behavior — the URL query redaction
requires a well-formed URL with scheme+host. Not a regression.
* perf(run_agent): cache _needs_thinking_reasoning_pad result per (provider, model, base_url)
Profile of a 31-turn synthetic agent run shows `_needs_thinking_reasoning_pad`
fires 495 times (~16 per turn) and each call ran 3 helper methods, each
hitting `base_url_host_matches` 1-4 times via `urlparse`. Total cost:
3,342 base_url_host_matches calls + 3,373 urlparse calls accounting for
~36ms of agent-loop overhead (~7% of the entire post-network work).
Provider / model / base_url don't change during a conversation except via
`switch_model` and fallback activation — both of which already overwrite
those attributes atomically. Cache the result on a tuple key; since the
key is derived from the very fields that would change, the cache
auto-invalidates on the next read after a switch. No manual invalidation
needed in switch_model / _try_activate_fallback.
Profile A/B (31-turn cached-config agent run):
BEFORE AFTER delta
_needs_thinking_reasoning_pad cum 18ms 1ms -94%
_copy_reasoning_content_for_api cum 17ms 1ms -94%
base_url_host_matches calls 3,342 372 -89%
urlparse calls 3,373 403 -88%
total function calls 296k 223k -25%
Verified:
- tests/run_agent/test_deepseek_reasoning_content_echo.py: 36/36 pass
- tests/run_agent/ (full): 1383/1383 pass + 3 skipped
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4 changed files with 165 additions and 42 deletions
133
agent/redact.py
133
agent/redact.py
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@ -321,6 +321,15 @@ def redact_sensitive_text(text: str, *, force: bool = False, code_file: bool = F
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patterns when the text is known to be source code (e.g. MAX_TOKENS=***
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constants, "apiKey": "test" fixtures). Prefix patterns, auth headers,
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private keys, DB connstrings, JWTs, and URL secrets are still redacted.
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Performance: each regex pattern is gated behind a cheap substring
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pre-check (e.g. ``"=" in text`` for ENV assignments, ``"://" in text``
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for URLs, ``"eyJ" in text`` for JWTs). On a typical hermes log line
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(no secrets) this drops the 13-pattern scan from ~5.6us to ~1.8us per
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record (-68%). The pre-checks are conservative — false positives
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still run the full regex, which then doesn't match. False negatives
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are impossible because every regex requires the gated substring to
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match.
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"""
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if text is None:
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return None
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@ -331,68 +340,122 @@ def redact_sensitive_text(text: str, *, force: bool = False, code_file: bool = F
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if not (force or _REDACT_ENABLED):
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return text
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# Known prefixes (sk-, ghp_, etc.)
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text = _PREFIX_RE.sub(lambda m: _mask_token(m.group(1)), text)
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# Known prefixes (sk-, ghp_, etc.) — gate on substring presence
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if _has_known_prefix_substring(text):
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text = _PREFIX_RE.sub(lambda m: _mask_token(m.group(1)), text)
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# ENV assignments: OPENAI_API_KEY=*** (skip for code files — false positives)
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if not code_file:
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def _redact_env(m):
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name, quote, value = m.group(1), m.group(2), m.group(3)
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return f"{name}={quote}{_mask_token(value)}{quote}"
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text = _ENV_ASSIGN_RE.sub(_redact_env, text)
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if "=" in text:
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def _redact_env(m):
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name, quote, value = m.group(1), m.group(2), m.group(3)
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return f"{name}={quote}{_mask_token(value)}{quote}"
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text = _ENV_ASSIGN_RE.sub(_redact_env, text)
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# JSON fields: "apiKey": "***" (skip for code files — false positives)
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def _redact_json(m):
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key, value = m.group(1), m.group(2)
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return f'{key}: "{_mask_token(value)}"'
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text = _JSON_FIELD_RE.sub(_redact_json, text)
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if ":" in text and '"' in text:
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def _redact_json(m):
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key, value = m.group(1), m.group(2)
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return f'{key}: "{_mask_token(value)}"'
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text = _JSON_FIELD_RE.sub(_redact_json, text)
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# Authorization headers
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text = _AUTH_HEADER_RE.sub(
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lambda m: m.group(1) + _mask_token(m.group(2)),
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text,
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)
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# Authorization headers — _AUTH_HEADER_RE is "Authorization: Bearer ..."
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# case-insensitive, so "uthorization" is the cheapest substring gate that
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# covers both "Authorization" and "authorization" without a casefold().
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if "uthorization" in text or "UTHORIZATION" in text:
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text = _AUTH_HEADER_RE.sub(
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lambda m: m.group(1) + _mask_token(m.group(2)),
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text,
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)
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# Telegram bot tokens
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def _redact_telegram(m):
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prefix = m.group(1) or ""
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digits = m.group(2)
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return f"{prefix}{digits}:***"
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text = _TELEGRAM_RE.sub(_redact_telegram, text)
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# Telegram bot tokens — pattern requires ":<token>" with digits prefix
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if ":" in text:
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def _redact_telegram(m):
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prefix = m.group(1) or ""
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digits = m.group(2)
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return f"{prefix}{digits}:***"
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text = _TELEGRAM_RE.sub(_redact_telegram, text)
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# Private key blocks
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text = _PRIVATE_KEY_RE.sub("[REDACTED PRIVATE KEY]", text)
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if "BEGIN" in text and "-----" in text:
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text = _PRIVATE_KEY_RE.sub("[REDACTED PRIVATE KEY]", text)
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# Database connection string passwords
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text = _DB_CONNSTR_RE.sub(lambda m: f"{m.group(1)}***{m.group(3)}", text)
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if "://" in text:
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text = _DB_CONNSTR_RE.sub(lambda m: f"{m.group(1)}***{m.group(3)}", text)
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# JWT tokens (eyJ... — base64-encoded JSON headers)
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text = _JWT_RE.sub(lambda m: _mask_token(m.group(0)), text)
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if "eyJ" in text:
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text = _JWT_RE.sub(lambda m: _mask_token(m.group(0)), text)
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# URL userinfo (http(s)://user:pass@host) — redact for non-DB schemes.
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# DB schemes are handled above by _DB_CONNSTR_RE.
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text = _redact_url_userinfo(text)
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if "://" in text:
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text = _redact_url_userinfo(text)
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# URL query params containing opaque tokens (?access_token=…&code=…)
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text = _redact_url_query_params(text)
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# URL query params containing opaque tokens (?access_token=…&code=…)
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if "?" in text:
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text = _redact_url_query_params(text)
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# Form-urlencoded bodies (only triggers on clean k=v&k=v inputs).
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text = _redact_form_body(text)
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if "&" in text and "=" in text:
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text = _redact_form_body(text)
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# Discord user/role mentions (<@snowflake_id>)
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text = _DISCORD_MENTION_RE.sub(lambda m: f"<@{'!' if '!' in m.group(0) else ''}***>", text)
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if "<@" in text:
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text = _DISCORD_MENTION_RE.sub(lambda m: f"<@{'!' if '!' in m.group(0) else ''}***>", text)
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# E.164 phone numbers (Signal, WhatsApp)
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def _redact_phone(m):
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phone = m.group(1)
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if len(phone) <= 8:
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return phone[:2] + "****" + phone[-2:]
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return phone[:4] + "****" + phone[-4:]
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text = _SIGNAL_PHONE_RE.sub(_redact_phone, text)
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if "+" in text:
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def _redact_phone(m):
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phone = m.group(1)
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if len(phone) <= 8:
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return phone[:2] + "****" + phone[-2:]
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return phone[:4] + "****" + phone[-4:]
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text = _SIGNAL_PHONE_RE.sub(_redact_phone, text)
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return text
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# Substrings used to gate ``_PREFIX_RE`` execution. If none of these appear in
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# the input string, the prefix regex cannot match anything, so we skip it.
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# False positives are fine (they just run the regex, which then matches
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# nothing) — the bound is "no false negatives" and that holds because every
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# pattern in ``_PREFIX_PATTERNS`` has at least one of these as a literal
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# substring of its leading characters.
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#
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# Derived automatically from ``_PREFIX_PATTERNS`` at module load time so a
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# future PR that adds a new prefix to the regex list can't silently break
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# the screen.
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def _extract_literal_prefix(pattern: str) -> str:
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"""Return the leading literal characters of a regex pattern.
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Stops at the first regex metacharacter (``[``, ``(``, ``\\``, ``.``,
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``?``, ``*``, ``+``, ``|``, ``{``, ``^``, ``$``). Returns the literal
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that any match of the pattern MUST contain as a substring, so the
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pre-screen never produces false negatives.
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"""
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meta = "[(\\.?*+|{^$"
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for i, ch in enumerate(pattern):
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if ch in meta:
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return pattern[:i]
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return pattern
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_PREFIX_SUBSTRINGS = tuple(
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_extract_literal_prefix(p) for p in _PREFIX_PATTERNS
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)
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def _has_known_prefix_substring(text: str) -> bool:
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"""Return True if ``text`` contains any known credential prefix substring.
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Used as a cheap pre-check before invoking the expensive ``_PREFIX_RE``.
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"""
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return any(p in text for p in _PREFIX_SUBSTRINGS)
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class RedactingFormatter(logging.Formatter):
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"""Log formatter that redacts secrets from all log messages."""
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