Intelligent Hospitality Agent for Personalized Guest Services
This challenge involves building an advanced agentic system designed to enhance guest experiences and streamline hotel operations. You will leverage the OpenAI Agents SDK to create a multi-faceted AI assistant capable of personalized guest interactions, dynamic service recommendations, and backend system automation. The agent will manage guest requests, integrate with existing hotel management systems (simulated), and learn from guest preferences stored in a vector database to provide truly bespoke service. This project emphasizes modern agent design, tool utilization, memory management, and robust observability for production-grade AI.
What you are building
The core problem, expected build, and operating context for this challenge.
This challenge involves building an advanced agentic system designed to enhance guest experiences and streamline hotel operations. You will leverage the OpenAI Agents SDK to create a multi-faceted AI assistant capable of personalized guest interactions, dynamic service recommendations, and backend system automation. The agent will manage guest requests, integrate with existing hotel management systems (simulated), and learn from guest preferences stored in a vector database to provide truly bespoke service. This project emphasizes modern agent design, tool utilization, memory management, and robust observability for production-grade AI.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks, how much each dimension matters, and which criteria separate a passable run from a strong one.
Correct tool usage
Agent must correctly identify and call the necessary tools for a given request.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Personalization via Milvus
Agent must demonstrate retrieval and use of personalized information from Milvus in at least 70% of relevant scenarios.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Request Fulfillment Accuracy
Percentage of requests correctly understood and acted upon by the agent (0-1). • target: 0.9 • range: 0.75-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Response Personalization
Score reflecting how well responses are tailored using guest data (0-1). • target: 0.85 • range: 0.7-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Langfuse Trace Completeness
Percentage of agent interactions fully traceable in Langfuse (0-1). • target: 1 • range: 0.9-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Master the OpenAI Agents SDK for building robust, autonomous agents, focusing on defining tools, assistant configuration, and thread management for multi-turn conversations.
Implement long-term memory for the agent using Milvus, storing and retrieving vectorized guest preferences, past requests, and feedback for personalized interactions.
Design and register custom tools (functions) within the OpenAI Agents SDK for simulating hotel operations like 'book_restaurant', 'request_concierge_service', 'check_in_guest', and 'retrieve_guest_profile'.
Utilize Adept's workflow automation capabilities (simulated through API calls) to trigger backend actions based on agent decisions, such as updating booking systems or scheduling staff tasks.
Orchestrate complex agent behaviors to handle nuanced guest requests, involving multiple tool calls, information synthesis from Milvus, and decision-making by the OpenAI o3 model.
Integrate Langfuse for end-to-end observability, tracing agent decisions, tool calls, LLM inputs/outputs, and intermediate thoughts, enabling effective debugging and performance monitoring.
[ok] Wrote CHALLENGE.md
[ok] Wrote .versalist.json
[ok] Wrote eval/examples.json
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