README.md

metadata

title: Support Ticket Routing
emoji: 🎫
colorFrom: blue
colorTo: indigo
sdk: docker
pinned: false
app_port: 8000
license: mit
tags:
  - openenv
  - reinforcement-learning
  - llm-agents
base_path: /web

🎫 Customer Support Ticket Routing Environment

📝 Description and Motivation

This environment simulates a production-grade customer support triage system. Automated agents are tasked with analyzing raw customer queries and routing them to the appropriate department: Billing, Tech, or Sales.

In real-world scenarios, misrouting leads to high churn and operational costs. This benchmark measures the ability of LLM-based agents to perform high-precision classification in a restricted environment compliant with the openenv-core SDK.

🎯 Environment Specification

Action Space

• action_type: Literal["route", "search"]
• department: Optional[str] — Required for route action. Valid values: "Billing", "Tech", "Sales".

Observation Space

• ticket_id: Unique tracking ID (e.g., T1, T4).
• content: The raw text string of the customer's request.
• search_result: Contextual data retrieved from the internal database (if the search action is invoked).
• available_departments: A list of valid routing targets.

Reward Function

To facilitate stable training and clear evaluation metrics, this environment uses strictly bounded rewards:

• 0.99: Correct Department Routing.
• 0.01: Incorrect Department Routing.
• -0.05: Search Penalty (Encourages efficiency unless context is truly needed).

🏁 Tasks and Difficulty

Task ID	Tickets	Description
easy	1	Clear keywords (e.g., "Refund", "Invoice").
medium	2	Standard conversational support language.
hard	3	Complex queries involving API logs and technical stack traces.

🚀 Setup & Benchmarking

1. Installation

pip install openenv-core uvicorn openai

2. Run Local Validation

Ensure your local setup matches the competition requirements:

openenv validate

3. Run Baseline Inference

Execute the provided baseline using the Hugging Face Router and the Qwen2.5-72B model:

export HF_TOKEN="your_huggingface_token"
python inference.py

🛠️ Technical Architecture

• Backend: Python FastAPI serving openenv-core compatible endpoints.
• Infrastructure: Containerized deployment via Docker on Hugging Face Spaces.
• Models: Pydantic-based state and action validation.

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Submission for the Scaler Meta PyTorch Hackathon. Environment ID: support_env | Powered by OpenEnv SDK.