aiq.data_models.profiler

Classes

PromptCachingConfig
BottleneckConfig
ConcurrencySpikeConfig
PrefixSpanConfig
ProfilerConfig

Module Contents

class PromptCachingConfig(/, **data: Any)

Bases: pydantic.BaseModel

enable: bool = False

min_frequency: float = 0.5

class BottleneckConfig(/, **data: Any)

Bases: pydantic.BaseModel

enable_simple_stack: bool = False

enable_nested_stack: bool = False

class ConcurrencySpikeConfig(/, **data: Any)

Bases: pydantic.BaseModel

enable: bool = False

spike_threshold: int = 1

class PrefixSpanConfig(/, **data: Any)

Bases: pydantic.BaseModel

enable: bool = False

min_support: float = 2

min_coverage: float = 0

max_text_len: int = 1000

top_k: int = 10

chain_with_common_prefixes: bool = False

class ProfilerConfig(/, **data: Any)

Bases: pydantic.BaseModel

token_usage_forecast: bool = False

token_uniqueness_forecast: bool = False

workflow_runtime_forecast: bool = False

compute_llm_metrics: bool = False

csv_exclude_io_text: bool = False

prompt_caching_prefixes: PromptCachingConfig

bottleneck_analysis: BottleneckConfig

concurrency_spike_analysis: ConcurrencySpikeConfig

prefix_span_analysis: PrefixSpanConfig