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the manager is passed as `manager_agent` and the four\nspecialists as `agents`.\n\n## Setup\n\nRequires Python 3.10 – 3.13 (CrewAI does not support 3.14 yet).\n\n```bash\npython3.12 -m venv .venv\n.venv/bin/pip install -r requirements.txt\ncp \"Customer Support with Multi-Agent System/task/.env.example\" \"Customer Support with Multi-Agent System/task/.env\"\n# then put your OpenAI key into task/.env\n```\n\n## Run\n\n```bash\ncd \"Customer Support with Multi-Agent System/task\"\npython support_crew.py            # press Enter for the demo tickets\n```\n\nOr feed a ticket as JSON:\n\n```bash\necho '{\"ticket_id\": \"TKT-999\", \"customer_id\": \"CUST001\", \"priority\": \"high\", \"issue\": \"Application crashes when exporting data\"}' | python support_crew.py\n```\n\n## Tests\n\n```bash\ncd \"Customer Support with Multi-Agent System/task\"\npython tests.py\n```\n\n10 tests cover the tools; the 11th runs eight tickets through the full crew and checks routing\nand the customer-facing resolution.\n\n## Implementation note\n\nThe support task is intentionally created **without** `agent=manager_agent`. In CrewAI's hierarchical\nprocess the manager always receives the task first, but `Crew._update_manager_tools` scopes the\nmanager's delegation tool to `[task.agent]` when one is set – so pinning the task to the manager\nwould let it delegate only to itself. Leaving the agent unset gives the manager delegation tools\nfor all four specialists.\n","readmeExcerpt":"Hierarchical Customer Support with a Multi-Agent System A customer-support system built with $1 that demonstrates **hierarchical orchestration**: a manager agent analyses incoming support tickets and delegates each one to the right specialist, who resolves it with domain-specific tools backed by mock databases. Hyperskill project: *Customer Support with Multi-Agent System*. 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