Robert Helewka
64fb83257d
- Add 202512_GenesysCX TEI study (config, seed data, notebooks, README) with NPV $10.8M / ROI 266% including AI-token cost line - Add explicit `key` parameter to all chart wrappers in app/components to prevent StreamlitDuplicateElementId errors when the same figure type renders across Summary/Benefits/Costs tabs - Render benefits bar and cost pie charts on their respective tabs - Add benefits_vs_costs_by_year chart wrapper
88 lines
2.9 KiB
Python
88 lines
2.9 KiB
Python
"""
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Genesys AI Experience token meters and pricing.
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Every meter carries a :class:`Confidence` flag so the UI can distinguish
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published Genesys rates from estimates and unknowns. Rates here are
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*planning inputs* — this tool explicitly does not replace contractual
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pricing (see README, Non-Goals).
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from enum import Enum
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class MeterType(Enum):
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PER_USER_PER_MONTH = "per_user_per_month"
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PER_INTERACTION = "per_interaction"
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PER_MINUTE = "per_minute"
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PER_MESSAGE = "per_message"
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PER_SUMMARY = "per_summary"
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class Confidence(Enum):
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CONFIRMED = "confirmed" # published Genesys rate
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ESTIMATED = "estimated" # reasonable industry assumption
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UNKNOWN = "unknown" # rate not yet sourced
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@property
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def icon(self) -> str:
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return {"confirmed": "🟢", "estimated": "🟡", "unknown": "🔴"}[self.value]
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@dataclass
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class TokenMeter:
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"""One Genesys AI feature's token meter.
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``units_per_token`` and ``tokens_per_unit`` are inverses; both are
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stored because the UI shows whichever reads more naturally (e.g.
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"17 minutes per token" vs "0.0588 tokens per minute"). For
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PER_USER_PER_MONTH meters ``units_per_token`` is 0.0 (n/a) and
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``tokens_per_unit`` is the flat tokens/user/month figure.
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"""
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feature: str
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meter_type: MeterType
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units_per_token: float
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tokens_per_unit: float
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confidence: Confidence
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notes: str
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source_url: str | None = None
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def __post_init__(self) -> None:
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if self.tokens_per_unit < 0:
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raise ValueError(f"{self.feature}: tokens_per_unit must be >= 0")
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if (
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self.meter_type is not MeterType.PER_USER_PER_MONTH
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and self.units_per_token > 0
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and self.tokens_per_unit > 0
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):
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product = self.units_per_token * self.tokens_per_unit
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if not 0.95 <= product <= 1.05:
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raise ValueError(
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f"{self.feature}: units_per_token ({self.units_per_token}) and "
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f"tokens_per_unit ({self.tokens_per_unit}) are not inverses"
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)
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@dataclass
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class TokenPricing:
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"""Per-region token pricing. Default is US list at $1/token."""
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region: str # "US", "AU", "EU", "APAC"
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list_rate_per_token: float = 1.0
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contracted_rate_per_token: float | None = None
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prepay_commit_tokens: int | None = None
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overage_rate_per_token: float | None = None
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def __post_init__(self) -> None:
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if self.list_rate_per_token < 0:
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raise ValueError(f"{self.region}: list rate must be >= 0")
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def effective_rate(self, use_contracted: bool = False) -> float:
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"""Contracted rate when requested and known, else list rate."""
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if use_contracted and self.contracted_rate_per_token is not None:
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return self.contracted_rate_per_token
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return self.list_rate_per_token
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