3f59b5c594
context_breakdown._chars_to_tokens and native_compaction._approx_tokens did raw chars//4, under-counting CJK/Cyrillic by 2-4x next to the conversation slice that already used estimate_tokens_rough — the /context pie chart mixed two estimators. Both now call the canonical. The four private `= 4` ratio constants import one CHARS_PER_TOKEN from agent/model_metadata.py. Estimates only feed UI and budgets; no prompt or message bytes change.
115 lines
5.5 KiB
Python
115 lines
5.5 KiB
Python
"""Configurable budget constants for tool result persistence.
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Per-tool resolution: pinned > config overrides > registry > default."""
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from dataclasses import dataclass, field
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from typing import Dict
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from agent.model_metadata import CHARS_PER_TOKEN
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# Never overridden; read_file=inf prevents infinite persist->read->persist loops.
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PINNED_THRESHOLDS: Dict[str, float] = {"read_file": float("inf")}
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# Single source of truth for the defaults; tool_result_storage.py imports these.
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DEFAULT_RESULT_SIZE_CHARS: int = 100_000
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DEFAULT_TURN_BUDGET_CHARS: int = 200_000
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DEFAULT_PREVIEW_SIZE_CHARS: int = 1_500
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# Tighter per-result default for ``mcp_`` tools: MCP servers routinely return
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# un-paginated 20-50K payloads that sail under the generic 100K threshold; spillover
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# keeps the full payload on disk. Config: ``tool_budget.mcp_result_size_chars``.
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DEFAULT_MCP_RESULT_SIZE_CHARS: int = 50_000
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# Same prefix the untrusted-content wrapper keys on (agent/tool_dispatch_helpers.py).
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MCP_TOOL_PREFIX: str = "mcp_"
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def _configured_mcp_result_size() -> int:
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"""Read ``tool_budget.mcp_result_size_chars`` via ``load_config_readonly`` (the
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sanctioned path; raw config.yaml parsing outside owner modules is test-guarded).
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Any error, missing key or non-positive value returns the built-in default.
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The ``tool_budget:`` block name is shared with the wider configurable-caps proposal (#80508) so the two
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can merge without a key rename.
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"""
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try:
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from hermes_cli.config import load_config_readonly
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data = load_config_readonly()
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block = data.get("tool_budget") if isinstance(data, dict) else None
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raw = block.get("mcp_result_size_chars") if isinstance(block, dict) else None
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if raw is not None and int(raw) > 0:
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return int(raw)
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except Exception:
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pass
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return DEFAULT_MCP_RESULT_SIZE_CHARS
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@dataclass(frozen=True)
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class BudgetConfig:
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"""Immutable budget constants: per-result threshold (``resolve_threshold``),
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per-turn aggregate (``turn_budget``) and inline snippet size (``preview_size``)."""
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default_result_size: int = DEFAULT_RESULT_SIZE_CHARS
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turn_budget: int = DEFAULT_TURN_BUDGET_CHARS
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preview_size: int = DEFAULT_PREVIEW_SIZE_CHARS
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mcp_result_size: int = DEFAULT_MCP_RESULT_SIZE_CHARS
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tool_overrides: Dict[str, int] = field(default_factory=dict)
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def resolve_threshold(self, tool_name: str) -> int | float:
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"""Priority: pinned -> tool_overrides -> mcp_ prefix -> registry per-tool -> default.
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MCP tools get ``mcp_result_size`` (no registry entry). MCP and registry values
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are capped at ``default_result_size`` so a context-scaled budget for a small
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model still constrains tools registering a fixed 100K ``max_result_size_chars``.
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For the default budget this is a no-op because both equal 100K; for a scaled-down budget it prevents
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a per-tool registry value from re-inflating the cap past the model's window (#23767).
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"""
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if tool_name in PINNED_THRESHOLDS:
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return PINNED_THRESHOLDS[tool_name]
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if tool_name in self.tool_overrides:
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return self.tool_overrides[tool_name]
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if tool_name.startswith(MCP_TOOL_PREFIX):
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return min(self.mcp_result_size, self.default_result_size)
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from tools.registry import registry
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registry_value = registry.get_max_result_size(tool_name, default=self.default_result_size)
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if registry_value == float("inf"):
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return registry_value
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return min(registry_value, self.default_result_size)
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# Default config -- matches the historical hardcoded behavior exactly.
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DEFAULT_BUDGET = BudgetConfig()
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# Same rough chars-per-token the estimator uses; a smaller divisor would UNDER-protect small models.
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_CHARS_PER_TOKEN: int = CHARS_PER_TOKEN
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# Window fraction ONE result / the WHOLE turn's tool output may occupy — well
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# under 1.0 since system prompt, schemas, history and the reply all compete.
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_PER_RESULT_WINDOW_FRACTION: float = 0.15
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_PER_TURN_WINDOW_FRACTION: float = 0.30
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# Floors so a tiny model still gets a usable result, never a 0-char budget.
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_MIN_RESULT_SIZE_CHARS: int = 8_000
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_MIN_TURN_BUDGET_CHARS: int = 16_000
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def budget_for_context_window(context_length: int | None) -> BudgetConfig:
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"""Return a BudgetConfig scaled to the model's context window: the fixed
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defaults suit 200K+ models but on 65K one result/turn can fill the window.
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The proportional value is clamped to the defaults as a CAP (large models
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stay byte-identical) and floored so a usable preview always survives.
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The fixed defaults (100K result / 200K turn chars) are correct for large (200K+ token) models but blind
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to small ones: on a 65K-token model a single tool result persisted at the 100K-char threshold, or a
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200K-char turn budget (~50K tokens), can by itself approach or exceed the whole window and force an
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oversized request (#23767).
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"""
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mcp_result_size = _configured_mcp_result_size()
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if not context_length or context_length <= 0:
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if mcp_result_size == DEFAULT_MCP_RESULT_SIZE_CHARS:
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return DEFAULT_BUDGET
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return BudgetConfig(mcp_result_size=mcp_result_size)
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window_chars = context_length * _CHARS_PER_TOKEN
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return BudgetConfig(
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default_result_size=max(_MIN_RESULT_SIZE_CHARS, min(int(window_chars * _PER_RESULT_WINDOW_FRACTION), DEFAULT_RESULT_SIZE_CHARS)),
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turn_budget=max(_MIN_TURN_BUDGET_CHARS, min(int(window_chars * _PER_TURN_WINDOW_FRACTION), DEFAULT_TURN_BUDGET_CHARS)),
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preview_size=DEFAULT_PREVIEW_SIZE_CHARS,
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mcp_result_size=mcp_result_size,
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)
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