README.md

metadata

title: Bug Triage OpenEnv
colorFrom: blue
colorTo: green
sdk: docker
app_port: 7860
tags:
  - openenv

Bug Triage OpenEnv

A typed OpenEnv environment for software bug triage. The agent must classify tickets, assign them to the right team, detect duplicates, request missing information, and escalate urgent incidents.

Why this environment

This is a real workflow, not a toy task. Software teams do bug triage every day, and progress can be measured step by step. The medium and hard tasks use varied, natural-language tickets instead of repeating a single template.

The environment includes:

• Typed Observation, Action, Reward, and State models with Pydantic
• Standard OpenEnv methods: reset(), step(), and state()
• Three deterministic tasks: easy, medium, and hard
• Programmatic graders with final task scores strictly in (0, 1)
• Dense rewards for partial progress

Observation and action space

Observation includes:

• Current ticket details
• Queue stats
• Available teams and components
• Steps used and remaining
• Partial score and last action result

Actions supported:

• classify
• assign
• mark_duplicate
• request_info
• defer
• close
• escalate_incident
• next_ticket

Tasks

bug_triage_easy

• Difficulty: easy
• 8 tickets
• Mostly clear bug reports with minimal duplicates

bug_triage_medium

• Difficulty: medium
• 15 tickets
• Mixed-quality reports with duplicates and missing information

bug_triage_hard

• Difficulty: hard
• 25 tickets
• Noisy tickets with SLA pressure and escalation trade-offs

Reward and grading

The reward function gives feedback during the episode, not only at the end.

It rewards:

• Correct severity, priority, and component classification
• Correct team assignment
• Correct duplicate handling
• Correct information requests
• Correct escalation of critical tickets

It penalizes:

• Invalid actions
• Repeated loop behavior
• Missing escalation on critical tickets
• Incorrect close or defer decisions

Each task has deterministic grader logic in server/graders/. For validator compatibility, final task scores are epsilon-clamped to a strict open interval:

• minimum: > 0.0
• maximum: < 1.0

Setup

Install dependencies:

python -m venv venv

Windows PowerShell:

venv\Scripts\Activate.ps1
pip install -r server/requirements.txt

macOS/Linux:

source venv/bin/activate
pip install -r server/requirements.txt

Validate:

openenv validate

Configure submission variables (required by inference.py):

API_BASE_URL=https://router.huggingface.co/v1
MODEL_NAME=Qwen/Qwen2.5-72B-Instruct
HF_TOKEN=<your_hf_token>

Run locally

Start the API:

uvicorn server.app:app --host 0.0.0.0 --port 7860

Web UI:

• Open http://127.0.0.1:7860/ (served from static/)

Main endpoints:

• GET /reset
• POST /reset (accepts empty body and optional JSON body)
• POST /step
• GET /state
• GET /tasks
• GET /health

Baseline inference

Submission runner:

python inference.py

inference.py emits strict structured stdout logs in this order only:

• [START] ...
• [STEP] ... (one line per call to step())
• [END] ...

By default, action= uses a compact human-readable format for easier scanning. Set OPENENV_LOG_ACTION_JSON=1 to emit raw JSON action payloads instead.

Deterministic offline baseline:

$env:OPENENV_OFFLINE = "1"
venv\Scripts\python.exe inference.py

Offline baseline snapshots are computed from the current shared policy and task fixtures. Use either of these to inspect live scores instead of relying on stale hardcoded numbers:

• python inference.py with OPENENV_OFFLINE=1
• GET /baseline

Submission check note:

• Ensure every task score is strictly between 0 and 1 (not exactly 0.0 or 1.0).

Docker and Hugging Face

Build:

docker build -t bug-triage-openenv .

Run:

docker run --rm -p 7860:7860 bug-triage-openenv

This repo is set up for a Docker-based Hugging Face Space and tagged with openenv.