Hermes-agent

hermes_cli/model_cost_guard.py

@@ -0,0 +1,134 @@
+"""Expensive-model confirmation helpers for model selection surfaces."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from decimal import Decimal, InvalidOperation
+from typing import Optional
+
+from agent.models_dev import ModelInfo
+
+
+INPUT_COST_WARNING_THRESHOLD = Decimal("20")
+OUTPUT_COST_WARNING_THRESHOLD = Decimal("100")
+GPT55_PRO_OPENROUTER_ID = "openai/gpt-5.5-pro"
+GPT55_SUGGESTION = "did you mean to select openai/gpt-5.5?"
+
+
+@dataclass(frozen=True)
+class ExpensiveModelWarning:
+    """Confirmation payload for models above Hermes' cost guardrail."""
+
+    model: str
+    provider: str
+    input_cost_per_million: Optional[Decimal]
+    output_cost_per_million: Optional[Decimal]
+    source: str
+    message: str
+
+
+def _to_decimal(value: object) -> Optional[Decimal]:
+    if value is None:
+        return None
+    try:
+        return Decimal(str(value))
+    except (InvalidOperation, ValueError):
+        return None
+
+
+def _format_money(value: Optional[Decimal]) -> str:
+    if value is None:
+        return "unknown"
+    return f"${value:.2f}/M"
+
+
+def _pricing_from_model_info(
+    model_info: Optional[ModelInfo],
+) -> tuple[Optional[Decimal], Optional[Decimal], str]:
+    if model_info is None or not model_info.has_cost_data():
+        return None, None, ""
+    return (
+        _to_decimal(model_info.cost_input),
+        _to_decimal(model_info.cost_output),
+        "models.dev",
+    )
+
+
+def expensive_model_warning(
+    model_name: str,
+    *,
+    provider: Optional[str] = None,
+    base_url: Optional[str] = None,
+    api_key: Optional[str] = None,
+    model_info: Optional[ModelInfo] = None,
+) -> Optional[ExpensiveModelWarning]:
+    """Return a warning payload when known pricing exceeds safety thresholds.
+
+    The guard only triggers when pricing is known. Callers should use this after
+    model resolution so aliases and provider-specific model IDs have settled.
+    """
+    model = (model_name or "").strip()
+    if not model:
+        return None
+
+    input_cost, output_cost, source = _pricing_from_model_info(model_info)
+    if input_cost is None and output_cost is None and provider:
+        try:
+            from agent.models_dev import get_model_info
+
+            input_cost, output_cost, source = _pricing_from_model_info(
+                get_model_info(provider, model)
+            )
+        except Exception:
+            pass
+    if input_cost is None and output_cost is None:
+        try:
+            from agent.usage_pricing import get_pricing_entry
+
+            entry = get_pricing_entry(
+                model,
+                provider=provider,
+                base_url=base_url,
+                api_key=api_key,
+            )
+        except Exception:
+            entry = None
+        if entry is not None:
+            input_cost = entry.input_cost_per_million
+            output_cost = entry.output_cost_per_million
+            source = entry.source
+
+    over_input = (
+        input_cost is not None and input_cost > INPUT_COST_WARNING_THRESHOLD
+    )
+    over_output = (
+        output_cost is not None and output_cost > OUTPUT_COST_WARNING_THRESHOLD
+    )
+    if not over_input and not over_output:
+        return None
+
+    lines = [
+        "!!! EXPENSIVE MODEL WARNING !!!",
+        "",
+        f"{model} has known pricing above Hermes' safety threshold.",
+        f"Input tokens: {_format_money(input_cost)}",
+        f"Output tokens: {_format_money(output_cost)}",
+        (
+            "Threshold: more than $20/M input tokens or more than "
+            "$100/M output tokens."
+        ),
+    ]
+    if source:
+        lines.append(f"Pricing source: {source}.")
+    if model.lower() == GPT55_PRO_OPENROUTER_ID:
+        lines.append(GPT55_SUGGESTION)
+    lines.append("Confirm only if you intend to use this model.")
+
+    return ExpensiveModelWarning(
+        model=model,
+        provider=(provider or "").strip(),
+        input_cost_per_million=input_cost,
+        output_cost_per_million=output_cost,
+        source=source or "unknown",
+        message="\n".join(lines),
+    )