# Notes: Jarvis Knowledge Brain Blueprint

## Current-State Findings
- Existing source domains already exist separately: conversations, documents, todos, tasks, forum posts.
- Current long-term memory only comes from conversation extraction via `UserMemory`.
- Current graph build path only uses indexed document chunks.
- Scheduler infrastructure already exists and can host daily brain-learning jobs.
- Frontend already exposes a `知识大脑` navigation entry, but it currently points to the graph page.

## Synthesized Findings

### What can be reused
- `memory_service` as a seed for conversation extraction and recall.
- `scheduler_service` as the base for daily learning workflows.
- `tag_service` as an early foundation for brain tags.
- Existing business tables as authoritative raw source records.

### What is missing
- Unified event layer across all source systems.
- Candidate memory layer between raw events and durable brain memory.
- Timeline-aware memory model with reinforcement / archival states.
- Retrieval path that combines long-term memory with recent relevant events.
- Brain-specific APIs and a dedicated frontend dashboard module.

### Phase 1 objective
- Build the minimum architecture needed for a real event-driven brain:
  - BrainEvent
  - BrainCandidate
  - BrainMemory
  - BrainTag and link tables
  - ingestion services
  - daily learning job
  - retrieval integration
  - brain dashboard APIs

## Additional Findings: Knowledge Parsing Normalization
- Current document ingestion parses each format separately and builds chunks directly from ParsedNode items.
- Current chunks already carry structural metadata, but there is no explicit parent-child chunk graph.
- The agreed direction is to use MinerU for PDF only, keep existing parsers for DOCX/XLSX/CSV/MD/TXT, and converge all outputs into structured markdown.
- normalized_content should be persisted on documents so preview, rebuild, and future chunking can reuse the same canonical text.
- Lightweight hierarchy should be represented in chunk metadata first, not in a new relational tree schema.
- Current DOCX upload failure in the running environment is caused by a missing python-docx installation in the active backend environment.