Class ControlLayerConfig

control_layer.py:99–124

All tunable parameters in one validated place. Pass a config dict or load from YAML/env — never hardcode in prod.

# =============================================================================

class ControlLayerConfig(BaseModel):
    """
    All tunable parameters in one validated place.
    Pass a config dict or load from YAML/env — never hardcode in prod.
    """
    total_tokens:       int   = Field(800,  ge=64,    le=128_000)
    max_attempts:       int   = Field(3,    ge=1,     le=10)
    max_input_chars:    int   = Field(2000, ge=64,    le=32_000)
    timeout_seconds:    float = Field(30.0, ge=0.01,  le=300.0)
    base_delay_ms:      float = Field(50.0, ge=1.0,   le=5_000.0)
    max_delay_ms:       float = Field(2000.0, ge=100.0, le=30_000.0)
    jitter_ms:          float = Field(25.0, ge=0.0,   le=500.0)
    # Circuit breaker
    cb_failure_threshold: int   = Field(5,    ge=2,  le=50)
    cb_recovery_seconds:  float = Field(30.0, ge=5.0, le=300.0)
    # Audit
    audit_log_path:     str   = Field("audit.jsonl")
    model_name:         str   = Field("cl100k_base")   # tiktoken encoding

    @field_validator("max_delay_ms")
    @classmethod
    def max_gt_base(cls, v, info):
        base = info.data.get("base_delay_ms", 50.0)
        if v < base:
            raise ValueError("max_delay_ms must be >= base_delay_ms")
        return v


class ResponseSchema(BaseModel):