Supervisor Worker Routing Decisionmedium

Supervisor Worker Routing Decision

medium Agents in Production 15 min

NumPy allowed · plain Python earns 10 bonus points

Interactive

Graph & Tree Traversal, Step by Step

Structure

Adjacency list (one node per line, "NODE: neighbor, neighbor")

Start node

Algorithm

visiting A -> visited order so far: [A]
queue now: [B, C]

Step 1 / 5

Both modes run the real algorithm from the linked practice problem, one step at a time -- edit the graph or pick different tree nodes and every step recomputes live.

Implement supervisor-worker routing, the decision logic behind a real supervisor-pattern multi-agent graph directing each incoming task to the right specialist worker node.

Task

Implement supervisor_route(task_category, worker_specialties, default_worker). Find the first worker (checking worker_specialties keys in sorted order for determinism) whose specialty list contains task_category. Return that worker's name, or default_worker if none match.

Function Signature

supervisor_route(task_category: str, worker_specialties: dict[str, list[str]], default_worker: str) -> str

Examples

Example 1: matched to specialist
Input: task_category = 'coding'
worker_specialties = {'coder': ['coding', 'debugging'], 'researcher': ['search']}
default_worker = 'general'
Output: 'coder'

Example 2: no match uses default
Input: task_category = 'cooking'
worker_specialties = {'coder': ['coding']}
default_worker = 'general'
Output: 'general'

Example 3: multiple workers alphabetical priority
Input: task_category = 'x'
worker_specialties = {'zeta': ['x'], 'alpha': ['x']}
default_worker = 'general'
Output: 'alpha'

Constraints

worker_specialties maps worker name -> list of handled categories

Python3Saved ✓

def supervisor_route(task_category, worker_specialties, default_worker):

# Your implementation here

pass

Case 1: matched to specialist

Input: task_category = 'coding'
worker_specialties = {'coder': ['coding', 'debugging'], 'researcher': ['search']}
default_worker = 'general'

Expected: 'coder'

Case 2: no match uses default

Input: task_category = 'cooking'
worker_specialties = {'coder': ['coding']}
default_worker = 'general'

Expected: 'general'

Case 3: multiple workers alphabetical priority

Input: task_category = 'x'
worker_specialties = {'zeta': ['x'], 'alpha': ['x']}
default_worker = 'general'

Expected: 'alpha'