This is the leap from a sequential script to a true, concurrent operating
system scheduler.

Right now, your Orchestrator evaluates the DAG one node at a time. If the
Architect designs a graph with 4 independent parsing utilities that all
eventually feed into a single database connector, the current Orchestrator
builds them sequentially (1, then 2, then 3, then 4).

By upgrading the DAG compiler to support Execution Tiers, the Orchestrator can
group nodes that have no dependencies on each other and fire their prompts off
to DeepSeek (or other specialized models) concurrently.

To make this happen, we need to execute a two-part surgery:

The Architect Upgrade: Teach it to delegate specific tasks to specialized
agents (e.g., deepseek-coder for core logic, deepseek-chat for data
formatting, or local llama3 for simple text filtering). Remember: We strictly
enforce that Gemma cannot be assigned coding tasks.

The Orchestrator Upgrade: Rewrite the Topological Sorter in compiler.js to
group nodes by "Depth Layers" and execute them using Promise.all().

Phase 1: The Architect (Delegation Matrix)

Open architect.js and update the --- PROVIDER ROUTING HEURISTICS --- in the
SYSTEM_PROMPT. We will teach it to act like a General Contractor assigning
subcontractors.

--- PROVIDER ROUTING HEURISTICS --- You must assign the 'provider' field based
on the cognitive load of the node: - > provider: deepseek-coder : MUST be used
for ALL logic, algorithm, and software engineering nodes. (Highly capable,
high cost). - > provider: local_llama3 : Use for simple, stateless text
transformation, regex extraction, or basic glue logic. (Fast, zero cost). - >
provider: gemma-2-9b-it : ONLY use for natural language summarization,
documentation, or semantic abstraction. STRONGLY FORBIDDEN from writing
executable code. --- HORIZONTAL BREAKDOWN (PARALLELISM) --- When designing the
architecture, do not chain nodes linearly unless they absolutely depend on
each other's output. If a task requires parsing 3 different file types, create
3 independent parser nodes that can be executed in parallel, feeding into 1
final aggregator node. 

Phase 2: The Parallel Execution Engine (compiler.js)

This is where the real engineering happens. We are going to replace
sortBottomUp (which returns a flat 1D array) with buildExecutionLayers (which
returns a 2D array of tiers).

Open compiler.js.

1. Replace the Sorter

Delete the entire function sortBottomUp(nodesMap) block and replace it with
this:

/ ========================================== // 3. EXECUTION TIER BUILDER
(PARALLELISM) // ========================================== function
buildExecutionLayers(nodesMap) { const layers = []; const resolvedNodes = new
Set(); const remainingNodes = new Set(nodesMap.keys()); while
(remainingNodes.size > 0) { const currentLayer = []; for (const nodeId of
remainingNodes) { const node = nodesMap.get(nodeId); // A node is ready if all
its dependencies are already in the 'resolvedNodes' set const isReady =
node.depends_on.every(dep => resolvedNodes.has(dep)); if (isReady) {
currentLayer.push(node); } } if (currentLayer.length === 0) { throw new
Error(`[FATAL] Circular dependency detected among: ${Array.from(remainingNodes)
.join(', ')}`); } // Add the current layer to the queue and mark nodes as
resolved layers.push(currentLayer); currentLayer.forEach(node => {
resolvedNodes.add(node.id); remainingNodes.delete(node.id); }); } return
layers; } 

2. Update the Orchestrator Loop

Now, scroll down to runOrchestrator(). We need to switch it from a standard
for loop to processing arrays of Promises concurrently.

Find this section in index.js or compiler.js (where it calls the sorter and
executes the loop):

/ Delete the old sort call // const buildOrder = sortBottomUp(validGraph); 

Replace the orchestrator logic with this:


The Multi-Agent Reality

With these changes, if you ask Hauki OS to "Build an offline document
summarizer for RTF, TXT, and MD files," the Architect will emit:

RTF_PARSER (Layer 1) -> deepseek-coder

TXT_PARSER (Layer 1) -> local_llama3

MD_PARSER (Layer 1) -> library (Linker intercepts)

SUMMARIZER (Layer 2) -> gemma-2-9b-it (Requires the 3 parsers above).

When the Orchestrator hits Layer 1, it will mount the MD Parser from disk,
fire a request to your local Llama-3 instance, and simultaneously fire a
request to the DeepSeek API. Layer 2 won't begin until Layer 1 is completely
resolved.