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97 lines
3.1 KiB
Python
97 lines
3.1 KiB
Python
"""
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IdeationAgent
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=============
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Stage 1 of the BookEngine pipeline: turn an ``IdeationContext`` into a
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``BookProposal`` that the user can confirm or edit before Spine generation.
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"""
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from __future__ import annotations
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from typing import Any
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from deeptutor.agents.base_agent import BaseAgent
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from deeptutor.utils.json_parser import parse_json_response
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from ..inputs import IdeationContext
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from ..models import BookProposal
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class IdeationAgent(BaseAgent):
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"""LLM call that proposes a book given the four-source IdeationContext."""
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def __init__(
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self,
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api_key: str | None = None,
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base_url: str | None = None,
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api_version: str | None = None,
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language: str = "en",
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binding: str = "openai",
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) -> None:
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super().__init__(
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module_name="book",
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agent_name="ideation_agent",
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api_key=api_key,
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base_url=base_url,
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api_version=api_version,
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language=language,
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binding=binding,
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)
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async def process(
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self,
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*,
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ideation_context: IdeationContext,
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) -> BookProposal:
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from ..blocks._language import language_directive
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system_prompt = self.get_prompt("system") or _FALLBACK_SYSTEM
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system_prompt = system_prompt.rstrip() + language_directive(self.language)
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user_template = self.get_prompt("user_template") or _FALLBACK_USER
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user_prompt = user_template.format(ideation_context=ideation_context.render())
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chunks: list[str] = []
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async for chunk in self.stream_llm(
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user_prompt=user_prompt,
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system_prompt=system_prompt,
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response_format={"type": "json_object"},
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stage="ideation",
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):
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chunks.append(chunk)
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raw = "".join(chunks)
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payload = parse_json_response(raw, logger_instance=self.logger, fallback={})
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if not isinstance(payload, dict):
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payload = {}
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return self._coerce_proposal(payload, ideation_context)
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@staticmethod
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def _coerce_proposal(data: dict[str, Any], ctx: IdeationContext) -> BookProposal:
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chapters_raw = data.get("estimated_chapters", 0) or 0
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try:
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estimated = max(2, min(8, int(chapters_raw)))
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except (TypeError, ValueError):
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estimated = 4
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title = str(data.get("title") or "Untitled Book").strip() or "Untitled Book"
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return BookProposal(
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title=title[:120],
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description=str(data.get("description") or "").strip(),
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scope=str(data.get("scope") or "").strip(),
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target_level=str(data.get("target_level") or "mixed").strip(),
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estimated_chapters=estimated,
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rationale=str(data.get("rationale") or "").strip(),
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)
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_FALLBACK_SYSTEM = (
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"Propose ONE coherent book that satisfies the learner's intent. "
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'Output JSON: {"title", "description", "scope", "target_level", '
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'"estimated_chapters", "rationale"}.'
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)
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_FALLBACK_USER = "{ideation_context}\n\nRespond with the JSON object only."
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__all__ = ["IdeationAgent"]
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