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⚡ Bolt: Optimized telemetry state and pricing configuration management #328

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⚡ Bolt: Optimized telemetry state and pricing configuration management #328

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47 changes: 29 additions & 18 deletions heidi_engine/telemetry.py
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Original file line number Diff line number Diff line change
Expand Up @@ -473,27 +473,39 @@ def load_pricing_config() -> Dict[str, Dict[str, float]]:
- Falls back to DEFAULT_PRICING
- Allows user to customize pricing per model

BOLT OPTIMIZATION:
Uses a thread-safe module-level cache (5.0s TTL) to avoid
redundant disk I/O and JSON parsing on high-frequency calls.

TUNABLE:
- Create pricing.json to override default prices
- Format: {"model_name": {"input": 0.5, "output": 1.5}}
- Prices are per 1M tokens
"""
pricing = DEFAULT_PRICING.copy()
global _pricing_cache, _pricing_check_ts
with _pricing_lock:
now = time.monotonic()
if _pricing_cache and (now - _pricing_check_ts) < 5.0:
return _pricing_cache.copy()

# Check for pricing config file
pricing_file = (
Path(PRICING_CONFIG_PATH) if PRICING_CONFIG_PATH else get_run_dir() / "pricing.json"
)
pricing = DEFAULT_PRICING.copy()

if pricing_file.exists():
try:
with open(pricing_file) as f:
custom = json.load(f)
pricing.update(custom)
except Exception as e:
print(f"[WARN] Failed to load pricing config: {e}", file=sys.stderr)
# Check for pricing config file
pricing_file = (
Path(PRICING_CONFIG_PATH) if PRICING_CONFIG_PATH else get_run_dir() / "pricing.json"
)

if pricing_file.exists():
try:
with open(pricing_file) as f:
custom = json.load(f)
pricing.update(custom)
except Exception as e:
print(f"[WARN] Failed to load pricing config: {e}", file=sys.stderr)

return pricing
_pricing_cache = pricing
_pricing_check_ts = now
return pricing.copy()
Comment on lines +485 to +508
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@gemini-code-assist gemini-code-assist Bot May 14, 2026

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high

The current implementation of load_pricing_config uses shallow copies (.copy()) for a nested dictionary structure (Dict[str, Dict[str, float]]). This is problematic because the inner dictionaries (e.g., {"input": 0.15, "output": 0.60}) remain shared between the cache, the DEFAULT_PRICING constant, and any caller that receives the returned value. If a caller or a subsequent update modifies an inner dictionary, it will inadvertently corrupt the global state and the cache.

Additionally, the cache is module-level but the pricing file path can be run-specific (via get_run_dir()). While the TTL mitigates this, it's safer to ensure the cache is isolated using copy.deepcopy.

    global _pricing_cache, _pricing_check_ts
    with _pricing_lock:
        now = time.monotonic()
        if _pricing_cache and (now - _pricing_check_ts) < 5.0:
            return copy.deepcopy(_pricing_cache)

        # Use deepcopy to ensure isolation from the module-level constant
        pricing = copy.deepcopy(DEFAULT_PRICING)

        # Check for pricing config file
        pricing_file = (
            Path(PRICING_CONFIG_PATH) if PRICING_CONFIG_PATH else get_run_dir() / "pricing.json"
        )

        if pricing_file.exists():
            try:
                with open(pricing_file) as f:
                    custom = json.load(f)
                    pricing.update(custom)
            except Exception as e:
                print(f"[WARN] Failed to load pricing config: {e}", file=sys.stderr)

        _pricing_cache = pricing
        _pricing_check_ts = now
        return copy.deepcopy(pricing)



def estimate_cost(input_tokens: int, output_tokens: int, model: str) -> float:
Expand Down Expand Up @@ -732,11 +744,6 @@ def get_state(run_id: Optional[str] = None) -> Dict[str, Any]:
"usage": get_default_usage(),
}

# BOLT OPTIMIZATION: Check thread-safe state cache
cached = _state_cache.get(target_run_id, state_file)
if cached:
return cached

try:
with open(state_file) as f:
state = json.load(f)
Expand Down Expand Up @@ -1372,6 +1379,10 @@ def stage_context(stage: str, round_num: int, message: str, **kwargs):
_gpu_check_ts = 0.0
_gpu_lock = threading.Lock()

_pricing_cache: Dict[str, Dict[str, float]] = {}
_pricing_check_ts = 0.0
_pricing_lock = threading.Lock()

_event_ts_cache: Dict[str, str] = {}
_event_ts_check_ts: Dict[str, float] = {} # run_id -> ts
_event_lock = threading.Lock()
Expand Down