 mrhavens
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be64111515
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feat: Issue #20 - Purpose-Based Agent Selection
Created purpose-specific writing agents:
- purpose_writers.py with 6 specialized agents:
- TutorialWriter: Hands-on learning (steps, exercises, encouragement)
- ExplainerWriter: Conceptual understanding (analogies, mental models)
- TransformationWriter: Personal change (emotional honesty, journey)
- EvidenceWriter: Data-driven decisions (evidence, tradeoffs)
- ReferenceWriter: Comprehensive reference (completeness, accuracy)
- VisionaryWriter: Inspirational content (emotion, vision)
Each agent has:
- 100+ line specialized system prompt
- Purpose-specific writing rules
- Structure guidance
- Tone guidance
- Example phrases
Factory functions:
- get_writer_for_purpose(purpose) → BaseAgent
- select_writer_agent(purpose) → str
- list_available_writers() → dict
This completes Issue #20.
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2026-03-13 22:26:24 +00:00 |
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mrhavens
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dec5aae09a
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Wire up all agents with LLM calls
- Worldsmith, Character Lead, Voice, Editor agents now call LLM
- All nonfiction agents wired (Researcher, Analyst, Writer, FactChecker, Editor)
- Orchestrator fully wired with agent pipeline
- Add python-dotenv dependency
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2026-03-12 18:42:15 +00:00 |
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mrhavens
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40378ad65e
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Initial commit: Opus Orchestrator AI - Full-flow book generation
- LangGraph workflow orchestration
- CrewAI agent crews (Fiction Fortress & Nonfiction Fortress)
- PydanticAI schema validation
- Fiction agents: Architect, Worldsmith, Character Lead, Voice, Editor
- Nonfiction agents: Researcher, Analyst, Writer, Fact-Checker, Editor
- Complete schema definitions for books, chapters, critiques
- Configuration management
- Basic test suite
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2026-03-12 17:45:05 +00:00 |
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