tomevault-io Data Flow
"Rooms are nodes. Exits are edges. Thrown objects are messages."
MOOLLM's approach to building processing pipelines using rooms and objects. The filesystem IS the data flow network.
The Pattern
- Rooms are processing stages (nodes)
- Exits connect stages (edges)
- Objects flow through as messages
- THROW sends objects through exits
- INBOX receives incoming objects
- OUTBOX stages outgoing objects
Commands
| Command | Effect |
|---|---|
THROW obj exit |
Send object through exit to destination |
INBOX |
List items waiting to be processed |
NEXT |
Get next item from inbox (FIFO) |
PEEK |
Look at next item without removing |
STAGE obj exit |
Add object to outbox for later throw |
FLUSH |
Throw all staged objects |
FLUSH exit |
Throw staged objects for specific exit |
Room Structure
stage/
├── ROOM.yml # Config and processor definition
├── inbox/ # Incoming queue (FIFO)
├── outbox/ # Staged for batch throwing
└── door-next/ # Exit to next stage
Processor Types
Script (Deterministic)
processor:
type: script
command: "python parse.py ${input}"
LLM (Semantic)
processor:
type: llm
prompt: |
Analyze this document:
- Extract key entities
- Summarize in 3 sentences
Hybrid
processor:
type: hybrid
pre_process: "extract.py ${input}"
llm_prompt: "Analyze extracted data"
post_process: "format.py ${output}"
Mix and match. LLM for reasoning, scripts for transformation.
Example Pipeline
uploads/ # Raw files land here
├── inbox/
│ ├── doc-001.pdf
│ └── doc-002.pdf
└── door-parser/
parser/ # Extract text
├── script: parse.py
└── door-analyzer/
analyzer/ # LLM analyzes
├── prompt: "Summarize..."
├── door-output/
└── door-errors/
output/ # Final results
└── inbox/
├── doc-001-summary.yml
└── doc-002-summary.yml
Processing Loop
> ENTER parser
Inbox: 2 items waiting.
> NEXT
Processing doc-001.pdf...
Text extracted.
> STAGE doc-001.txt door-analyzer
Staged.
> FLUSH
Throwing 2 items through door-analyzer...
Fan-Out (one-to-many)
routing_rules:
- if: "priority == 'high'"
throw_to: door-fast-track
- if: "type == 'archive'"
throw_to: door-archive
- default: door-standard
Fan-In (many-to-one)
batch_size: 10
on_batch_complete: |
Combine all results
Generate summary report
THROW report.yml door-output
Kilroy Mapping
| MOOLLM | Kilroy |
|---|---|
| Room | Node |
| Exit | Edge |
| THROW | Message passing |
| inbox/ | Input queue |
| Script processor | Deterministic module |
| LLM processor | LLM node |
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