IB-WP-0019-T03: rate-table cost computation

Ship a starter model rate table at src/infospace_bench/model_rates.yaml
(prompt_per_1k / completion_per_1k for the OpenRouter models we have
actually touched: gpt-4o, gpt-4o-mini, gpt-4-turbo, claude 3.5 sonnet
and haiku, claude 3 opus, gemini 1.5 flash/pro, llama 3.1 70b) and a
load_rate_table() / estimate_cost_usd() pair that overlays an optional
<workspace>/model-rates.yaml on top of the bundled defaults.

generate run now passes a workspace-aware cost_resolver into
record_run_usage, so cost_usd_estimated lands on every usage bucket
whose model matches the table. Adapter-returned cost still wins
(cost_status="known"); rate-table cost is reported under
cost_status="estimated"; unmatched models are recorded as
cost_status="unknown" rather than silently zeroed. Rate-table file is
listed in pyproject.toml package-data so pip-installed users keep the
defaults.

106 tests pass.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

src/infospace_bench/budget.py

@@ -15,10 +15,13 @@ import hashlib
 import json
 from datetime import datetime, timezone
 from pathlib import Path
-from typing import Any
+from typing import Any, Callable
 
 import yaml
 
+RATES_FILENAME = "model-rates.yaml"
+_PACKAGE_RATES_PATH = Path(__file__).parent / "model_rates.yaml"
+
 BUDGET_DIR = Path("output/budget")
 PLANS_FILE = BUDGET_DIR / "plans.yaml"
 USAGE_FILE = BUDGET_DIR / "usage.yaml"
@@ -210,6 +213,76 @@ def read_usage_runs(root: str | Path) -> list[dict[str, Any]]:
     return list(payload.get("runs") or [])
 
 
+def load_rate_table(workspace: Path | str | None = None) -> dict[str, dict[str, float]]:
+    """Load the model rate table, with optional workspace override.
+
+    Returns a mapping ``model_id -> {prompt_per_1k, completion_per_1k}``. The
+    workspace override (``<workspace>/model-rates.yaml``) is overlaid on top of
+    the package default, so individual models can be tweaked without copying
+    the whole table.
+    """
+    rates: dict[str, dict[str, float]] = {}
+    for path in (_PACKAGE_RATES_PATH, _workspace_rate_path(workspace)):
+        if path is None or not path.is_file():
+            continue
+        try:
+            data = yaml.safe_load(path.read_text(encoding="utf-8"))
+        except yaml.YAMLError:
+            continue
+        if not isinstance(data, dict):
+            continue
+        for model, entry in (data.get("rates") or {}).items():
+            if not isinstance(entry, dict):
+                continue
+            prompt = _coerce_float(entry.get("prompt_per_1k"))
+            completion = _coerce_float(entry.get("completion_per_1k"))
+            if prompt is None and completion is None:
+                continue
+            rates[str(model)] = {
+                "prompt_per_1k": prompt if prompt is not None else 0.0,
+                "completion_per_1k": completion if completion is not None else 0.0,
+            }
+    return rates
+
+
+def estimate_cost_usd(
+    model: str,
+    prompt_tokens: int,
+    completion_tokens: int,
+    rate_table: dict[str, dict[str, float]],
+) -> float | None:
+    entry = rate_table.get(model)
+    if entry is None:
+        return None
+    prompt_rate = float(entry.get("prompt_per_1k") or 0.0)
+    completion_rate = float(entry.get("completion_per_1k") or 0.0)
+    cost = (prompt_tokens / 1000.0) * prompt_rate + (
+        completion_tokens / 1000.0
+    ) * completion_rate
+    return round(cost, 6)
+
+
+def make_cost_resolver(
+    workspace: Path | str | None,
+) -> Callable[[str, str, int, int], float | None]:
+    """Return a resolver suitable for ``record_run_usage(..., cost_resolver=...)``."""
+    rates = load_rate_table(workspace)
+
+    def _resolve(provider: str, model: str, prompt_tokens: int, completion_tokens: int) -> float | None:
+        if not model:
+            return None
+        return estimate_cost_usd(model, prompt_tokens, completion_tokens, rates)
+
+    return _resolve
+
+
+def _workspace_rate_path(workspace: Path | str | None) -> Path | None:
+    if workspace is None:
+        return None
+    candidate = Path(workspace) / RATES_FILENAME
+    return candidate
+
+
 def _coerce_float(value: Any) -> float | None:
     if value is None:
         return None

src/infospace_bench/generator.py

@@ -20,6 +20,7 @@ from .lifecycle import create_infospace, load_infospace, register_artifact
 from .openrouter import OpenRouterAssistedGenerationAdapter
 from .budget import (
     latest_plan_snapshot_id,
+    make_cost_resolver,
     record_plan_snapshot,
     record_run_usage,
 )
@@ -324,6 +325,15 @@ def _read_profile_name(root: Path) -> str:
     return str(state.get("profile") or DEFAULT_PROFILE)
 
 
+def _workspace_for(root: Path) -> Path:
+    """Resolve the workspace directory that contains this infospace.
+
+    The standard layout is ``<workspace>/infospaces/<slug>``, so the
+    workspace is two levels above the infospace root.
+    """
+    return root.parent.parent
+
+
 def run_generation(
     root: str | Path,
     *,
@@ -396,6 +406,7 @@ def run_generation(
             snapshot_id=latest_plan_snapshot_id(root_path),
             duration_seconds=duration_seconds,
             started_at=started_wall.isoformat(),
+            cost_resolver=make_cost_resolver(_workspace_for(root_path)),
         )
     return GenerationRunResult(
         root=str(root_path),

src/infospace_bench/model_rates.yaml

@@ -0,0 +1,41 @@
+# Default model rate table for cost estimation.
+#
+# Rates are best-effort OpenRouter list prices in USD per 1 000 tokens. Provider
+# rates drift; treat any cost computed from this table as an estimate
+# (cost_status="estimated") and refresh the table when prices change. Adapter-
+# returned cost always takes precedence over this table.
+#
+# Consumers can override entries by placing a `model-rates.yaml` with the same
+# top-level shape in their workspace directory (alongside `infospaces/`).
+schema_version: 1
+currency: USD
+source_url: https://openrouter.ai/models
+captured_at: "2026-05-17"
+rates:
+  openai/gpt-4o-mini:
+    prompt_per_1k: 0.00015
+    completion_per_1k: 0.00060
+  openai/gpt-4o:
+    prompt_per_1k: 0.0025
+    completion_per_1k: 0.01
+  openai/gpt-4-turbo:
+    prompt_per_1k: 0.01
+    completion_per_1k: 0.03
+  anthropic/claude-3.5-sonnet:
+    prompt_per_1k: 0.003
+    completion_per_1k: 0.015
+  anthropic/claude-3.5-haiku:
+    prompt_per_1k: 0.0008
+    completion_per_1k: 0.004
+  anthropic/claude-3-opus:
+    prompt_per_1k: 0.015
+    completion_per_1k: 0.075
+  google/gemini-1.5-flash:
+    prompt_per_1k: 0.000075
+    completion_per_1k: 0.0003
+  google/gemini-1.5-pro:
+    prompt_per_1k: 0.00125
+    completion_per_1k: 0.005
+  meta-llama/llama-3.1-70b-instruct:
+    prompt_per_1k: 0.00059
+    completion_per_1k: 0.00079