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78 lines
2.6 KiB
Python
78 lines
2.6 KiB
Python
"""Runtime config builder for ``QuestionPipeline``.
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Mirrors the shape used by :mod:`deeptutor.agents.research.request_config`,
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but with a much smaller surface — the question pipeline only needs a
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handful of knobs out of the service config:
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* ``exploring.max_iterations`` (int, default 8) — agentic-loop cap for the
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Explore phase.
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* ``exploring.tool_summarizer.enabled`` (bool, default True) — toggle the
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per-tool-result LLM reflection step that compresses raw tool output
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before downstream phases see it.
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* ``exploring.tool_summarizer.max_tokens`` (int, default 800) — token cap
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on each summarizer call.
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The helper is intentionally tolerant: missing keys / wrong types collapse
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to defaults so callers can pass any base config (e.g. ``main.yaml``)
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without first defining a ``capabilities.deep_question`` section.
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"""
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from __future__ import annotations
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from typing import Any
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def _read_int(source: dict[str, Any], key: str, default: int) -> int:
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value = source.get(key)
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if isinstance(value, int) and value > 0:
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return value
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return default
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def _read_bool(source: dict[str, Any], key: str, default: bool) -> bool:
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value = source.get(key)
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if isinstance(value, bool):
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return value
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return default
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def build_question_runtime_config(
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*,
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base_config: dict[str, Any] | None,
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) -> dict[str, Any]:
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"""Build the runtime_config dict passed to :class:`QuestionPipeline`.
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The pipeline reads its knobs from ``runtime_config["exploring"]`` —
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everything else in ``base_config`` is currently ignored by question.
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"""
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base = base_config if isinstance(base_config, dict) else {}
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capabilities = base.get("capabilities") if isinstance(base.get("capabilities"), dict) else {}
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question_root = (
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capabilities.get("deep_question")
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if isinstance(capabilities.get("deep_question"), dict)
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else {}
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)
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exploring_root = (
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question_root.get("exploring") if isinstance(question_root.get("exploring"), dict) else {}
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)
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summarizer_root = (
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exploring_root.get("tool_summarizer")
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if isinstance(exploring_root.get("tool_summarizer"), dict)
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else {}
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)
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exploring = {
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"max_iterations": _read_int(exploring_root, "max_iterations", 8),
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"tool_summarizer": {
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"enabled": _read_bool(summarizer_root, "enabled", True),
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"max_tokens": _read_int(summarizer_root, "max_tokens", 800),
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},
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}
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runtime_config = dict(base)
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runtime_config["exploring"] = exploring
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return runtime_config
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__all__ = ["build_question_runtime_config"]
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