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79 lines
2.1 KiB
Python
79 lines
2.1 KiB
Python
"""Helpers for reasoning about model context-window budgets."""
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from __future__ import annotations
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from typing import Any
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DEFAULT_CONTEXT_WINDOW_FALLBACK = 16_384
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MAX_EFFECTIVE_CONTEXT_WINDOW = 1_000_000
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LARGE_CONTEXT_MODEL_DEFAULT = 65_536
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KNOWN_LARGE_CONTEXT_MARKERS = (
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"gpt-4.1",
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"gpt-4o",
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"gpt-5",
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"o1",
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"o3",
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"o4",
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"claude",
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"gemini",
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"qwen",
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"deepseek",
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"moonshot",
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"kimi",
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)
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def coerce_positive_int(value: Any) -> int | None:
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"""Parse a positive integer from arbitrary input."""
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try:
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parsed = int(str(value).strip())
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except (TypeError, ValueError):
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return None
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return parsed if parsed > 0 else None
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def looks_like_large_context_model(model: str) -> bool:
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"""Return True when a model family is typically backed by a large window."""
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normalized = (model or "").strip().lower()
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return any(marker in normalized for marker in KNOWN_LARGE_CONTEXT_MARKERS)
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def default_context_window_for_model(
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*,
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model: str,
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max_tokens: Any = None,
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) -> int:
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"""Return the fallback window used when no explicit model metadata exists."""
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if looks_like_large_context_model(model):
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return LARGE_CONTEXT_MODEL_DEFAULT
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output_limit = coerce_positive_int(max_tokens) or 4096
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return max(DEFAULT_CONTEXT_WINDOW_FALLBACK, output_limit * 4)
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def resolve_effective_context_window(
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*,
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context_window: Any = None,
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model: str,
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max_tokens: Any = None,
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) -> int:
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"""Resolve the bounded history-planning window for the current model."""
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configured = coerce_positive_int(context_window)
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if configured is not None:
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return min(configured, MAX_EFFECTIVE_CONTEXT_WINDOW)
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return min(
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default_context_window_for_model(model=model, max_tokens=max_tokens),
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MAX_EFFECTIVE_CONTEXT_WINDOW,
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)
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__all__ = [
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"DEFAULT_CONTEXT_WINDOW_FALLBACK",
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"MAX_EFFECTIVE_CONTEXT_WINDOW",
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"LARGE_CONTEXT_MODEL_DEFAULT",
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"KNOWN_LARGE_CONTEXT_MARKERS",
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"coerce_positive_int",
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"default_context_window_for_model",
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"looks_like_large_context_model",
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"resolve_effective_context_window",
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]
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