234 lines
7.2 KiB
Python
234 lines
7.2 KiB
Python
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"""Research Integration for Nonfiction Generation.
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Integrates the research agent into the main nonfiction pipeline.
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"""
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from typing import Optional
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from dataclasses import dataclass
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from opus_orchestrator.nonfiction import ReaderPurpose
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@dataclass
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class ResearchRequest:
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"""A research request for the research agent."""
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topic: str
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subtopics: list[str]
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depth: str = "standard" # shallow, standard, deep
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include_academic: bool = False
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@dataclass
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class ResearchResult:
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"""Result from research agent."""
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summary: str
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key_findings: list[str]
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sources: list[str]
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gaps_identified: list[str]
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raw_data: dict
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class ResearchIntegrator:
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"""Integrates research into the nonfiction pipeline.
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Can be used at different stages:
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- Pre-writing: Gather research for the book
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- Per-chapter: Research specific topics
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- Verification: Check facts post-writing
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"""
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def __init__(self, research_agent=None):
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self.research_agent = research_agent
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async def research_for_book(
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self,
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concept: str,
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purpose: ReaderPurpose,
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depth: str = "standard",
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) -> ResearchResult:
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"""Conduct research for an entire book.
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Args:
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concept: The book concept/topic
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purpose: The reader purpose (determines research focus)
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depth: How deep to research
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Returns:
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ResearchResult with findings and sources
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"""
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# Determine research focus based on purpose
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research_focus = self._get_research_focus(purpose)
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# Build research queries
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queries = self._build_research_queries(concept, purpose)
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# This would call the actual research agent
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# For now, return a structured result
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return ResearchResult(
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summary=f"Research for {concept} focused on {research_focus}",
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key_findings=[
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"Finding 1 would go here",
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"Finding 2 would go here",
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],
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sources=["Source 1", "Source 2"],
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gaps_identified=["Gap 1", "Gap 2"],
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raw_data={},
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)
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def _get_research_focus(self, purpose: ReaderPurpose) -> str:
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"""Determine research focus based on purpose."""
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focus_map = {
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ReaderPurpose.LEARN_HANDS_ON: "best practices, tutorials, methods",
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ReaderPurpose.UNDERSTAND: "theories, concepts, explanations",
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ReaderPurpose.TRANSFORM: "case studies, success stories, methods",
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ReaderPurpose.DECIDE: "data, studies, comparisons, evidence",
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ReaderPurpose.REFERENCE: "comprehensive documentation, specifications",
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ReaderPurpose.BE_INSPIRED: "stories, journeys, examples",
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}
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return focus_map.get(purpose, "general information")
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def _build_research_queries(self, concept: str, purpose: ReaderPurpose) -> list[str]:
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"""Build research queries based on concept and purpose."""
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base_query = concept
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queries = [
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f"{base_query} overview",
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f"{base_query} {self._get_research_focus(purpose)}",
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]
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if purpose == ReaderPurpose.DECIDE:
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queries.extend([
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f"{base_query} pros and cons",
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f"{base_query} comparison",
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f"{base_query} research studies",
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])
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elif purpose == ReaderPurpose.TRANSFORM:
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queries.extend([
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f"{base_query} success stories",
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f"{base_query} case studies",
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f"{base_query} methods",
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])
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elif purpose == ReaderPurpose.UNDERSTAND:
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queries.extend([
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f"{base_query} theory",
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f"{base_query} concept explained",
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f"{base_query} how it works",
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])
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return queries
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async def research_chapter(
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self,
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chapter_topic: str,
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context: dict,
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) -> ResearchResult:
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"""Research a specific chapter.
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Args:
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chapter_topic: What this chapter is about
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context: Book context (concept, purpose, etc.)
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Returns:
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ResearchResult for this chapter
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"""
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# Research this specific topic
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queries = [
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f"{chapter_topic} overview",
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f"{chapter_topic} best practices",
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f"{chapter_topic} recent developments",
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]
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return ResearchResult(
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summary=f"Research for chapter: {chapter_topic}",
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key_findings=[],
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sources=[],
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gaps_identified=[],
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raw_data={},
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)
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def should_use_research(self, purpose: ReaderPurpose) -> bool:
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"""Determine if research should be used for this purpose.
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Args:
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purpose: The reader purpose
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Returns:
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Whether to use research
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"""
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# Research is valuable for these purposes
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research_worthwhile = [
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ReaderPurpose.UNDERSTAND,
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ReaderPurpose.DECIDE,
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ReaderPurpose.TRANSFORM,
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ReaderPurpose.LEARN_HANDS_ON,
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]
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return purpose in research_worthwhile
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def get_research_stages(self) -> list[str]:
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"""Get the stages where research can be integrated.
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Returns:
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List of stage names where research applies
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"""
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return [
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"pre_writing", # Research before writing begins
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"per_chapter", # Research each chapter
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"verification", # Verify facts after writing
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"enhancement", # Add research to strengthen content
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]
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def get_research_config_for_purpose(purpose: ReaderPurpose) -> dict:
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"""Get research configuration optimized for purpose.
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Args:
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purpose: The reader purpose
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Returns:
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Dict with research settings
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"""
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configs = {
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ReaderPurpose.LEARN_HANDS_ON: {
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"depth": "standard",
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"include_tutorials": True,
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"include_best_practices": True,
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"include_academic": False,
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},
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ReaderPurpose.UNDERSTAND: {
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"depth": "deep",
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"include_theories": True,
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"include_explanations": True,
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"include_academic": True,
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},
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ReaderPurpose.TRANSFORM: {
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"depth": "standard",
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"include_case_studies": True,
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"include_success_stories": True,
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"include_methods": True,
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},
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ReaderPurpose.DECIDE: {
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"depth": "deep",
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"include_studies": True,
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"include_data": True,
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"include_comparisons": True,
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"include_academic": True,
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},
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ReaderPurpose.REFERENCE: {
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"depth": "deep",
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"include_specifications": True,
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"include_documentation": True,
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"include_comprehensive": True,
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},
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ReaderPurpose.BE_INSPIRED: {
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"depth": "shallow",
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"include_stories": True,
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"include_journeys": True,
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"include_examples": True,
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},
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}
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return configs.get(purpose, {"depth": "standard"})
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