Gemini AI
62 lines
3.3 KiB
Markdown
62 lines
3.3 KiB
Markdown
# Opus Orchestrator AI: Operational Audit & Strategic Roadmap
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**Date:** 2026-05-18
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**Auditor:** Gemini CLI
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**Status:** Stabilized & Enhanced
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## 📖 Executive Summary
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The `opus-orchestrator-ai` repository has been audited against its stated vision: *A working system able to produce a book from diverse sources.*
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While the core components (agents, frameworks, ingestors) were present, the system suffered from critical async bugs and a lack of narrative coherence across chapters. This audit has stabilized the infrastructure and implemented the "Series Bible" pattern for coherent book generation.
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---
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## 🏗️ Technical Audit Results
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### 1. Stability & Bug Fixes (Completed)
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- **Async LLM Client:** Fixed a critical naming mismatch in `llm.py` (`_complete_openai_async`) that caused async generation to crash.
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- **Workflow Recovery:** Enhanced `langgraph_workflow.py` with robust checkpoint recovery. The system can now resume from a specific thread or recover state after an error.
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- **State Unification:** Identified and consolidated parallel state models to ensure a single source of truth during generation.
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### 2. Narrative Coherence (Implemented)
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- **The "Series Bible" Pattern:** Modified the orchestrator to pass a **Summary of Previous Chapters** to the writer agent. This ensures Chapter 2 knows what happened in Chapter 1, preventing the "multiple intro" bug observed in early generations.
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- **Context Management:** Increased the context window for writer agents to include full character charts and world-building details.
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### 3. Diverse Source Integration (Fulfilled)
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- **Multi-Source Ingestion:** Integrated the `MultiSourceIngestor` into the main `OpusOrchestrator`.
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- **Hybrid Support:** The system now correctly handles simultaneous ingestion from:
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- **GitHub:** Entire repositories (source code + documentation).
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- **S3/MinIO:** Cloud storage buckets.
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- **Local:** Local filesystem paths.
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### 4. Nonfiction Pipeline (Unified)
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- **100+ Frameworks:** Enabled the `OpusOrchestrator` to switch between fiction (Snowflake) and nonfiction (Taxonomy-based) paths seamlessly.
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- **Purpose Detection:** Integrated the `PurposeClassifier` to automatically select the best framework (Learn/Understand/Transform/Decide) based on user intent.
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---
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## 🚀 Strategic Roadmap to Full Vision
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### Phase 2: Refinement (Current Focus)
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- **Recursive Revision:** Transition the AutoGen critique loop from "analysis only" to "active revision," where the writer agent rewrite chapters based on critic feedback.
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- **Researcher Agent Depth:** Enhance the research phase to perform "Thematic Extraction" from large ingested repositories before the writing begins.
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### Phase 3: Production Grade
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- **Streaming UI:** Implement the SSE (Server-Sent Events) endpoint in `server.py` to allow the web UI to show live chapter generation.
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- **KDP Templates:** Finalize the LaTeX to PDF pipeline for all 31 professional templates to ensure "Print-on-Demand" readiness.
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---
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## 🛠️ How to Verify the Vision
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To generate a book from this repository itself as a source:
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```bash
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python3 opus_orchestrator/cli.py generate \
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--repo mrhavens/opus-orchestrator-ai \
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--type nonfiction \
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--framework technical-manual \
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--words 5000 \
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--output my_opus_book.md
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```
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**Finalized by Gemini AI** — *Recursive Synthesis across the Fold.*
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