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77 lines
3.1 KiB
Python
77 lines
3.1 KiB
Python
"""Mastery Path capability — mastery-based tutoring driven by the chat loop.
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There is no bespoke state machine here anymore. The chat agent loop IS the
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tutor: this capability only marks the turn as mastery mode and resolves the
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active path id, then runs the standard agentic chat pipeline. The pipeline
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mounts the mastery tools (``mastery_status`` / ``mastery_quiz`` /
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``mastery_grade`` / ``mastery_assess`` / ``mastery_build``) and injects the
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tutor playbook; the pure engine in :mod:`deeptutor.learning` owns the hard,
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per-type mastery gate and the spaced-repetition arithmetic.
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Design axiom (shared with chat): the intelligence lives at the loop's exit —
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the model decides what to teach and how to question — while the gate that
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decides *whether the learner may advance* is a deterministic engine call.
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"""
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from __future__ import annotations
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import re
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from deeptutor.agents.chat.agentic_pipeline import AgenticChatPipeline
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from deeptutor.capabilities.mastery.tools import MASTERY_TOOL_NAMES
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from deeptutor.core.capability_protocol import BaseCapability, CapabilityManifest
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from deeptutor.core.context import UnifiedContext
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from deeptutor.core.stream_bus import StreamBus
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_UNSAFE_ID_CHARS = re.compile(r"[^A-Za-z0-9_-]")
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def _sanitize_path_id(raw: str) -> str:
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"""Make *raw* a safe storage key (matches ``LearningStore`` path guard)."""
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cleaned = _UNSAFE_ID_CHARS.sub("_", raw).strip("_")
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return cleaned or "default"
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def resolve_mastery_path_id(context: UnifiedContext) -> str:
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"""Resolve which learner-path the turn operates on.
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Prefers an explicit ``mastery_path_id`` set by the frontend (so the tutor
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and the build wizard / dashboard agree on one storage key), then a book
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reference, then the session id for an ad-hoc path built inside a chat.
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"""
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explicit = str(context.metadata.get("mastery_path_id") or "").strip()
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if explicit:
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return _sanitize_path_id(explicit)
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refs = (context.metadata or {}).get("book_references", [])
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if refs:
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ref = refs[0]
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if isinstance(ref, str) and ref.strip():
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return _sanitize_path_id(ref)
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if isinstance(ref, dict):
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candidate = str(ref.get("book_id") or ref.get("id") or "").strip()
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if candidate:
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return _sanitize_path_id(candidate)
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return _sanitize_path_id(str(context.session_id or "default"))
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class MasteryPathCapability(BaseCapability):
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manifest = CapabilityManifest(
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name="mastery_path",
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description=(
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"Mastery-based tutoring: the chat agent loop drives an adaptive "
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"mastery path with a hard, per-type mastery gate and spaced review."
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),
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stages=["responding"],
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tools_used=[*MASTERY_TOOL_NAMES, "rag", "read_source", "ask_user"],
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cli_aliases=["mastery"],
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)
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async def run(self, context: UnifiedContext, stream: StreamBus) -> None:
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context.metadata["mastery_mode"] = True
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context.metadata["mastery_path_id"] = resolve_mastery_path_id(context)
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pipeline = AgenticChatPipeline(language=context.language)
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await pipeline.run(context, stream)
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__all__ = ["MasteryPathCapability", "resolve_mastery_path_id"]
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